Model uncertainty and asset return predictability: an application of Bayesian model averaging

We investigate model uncertainty associated with predictive regressions employed in asset return forecasting research. We use simple combination and Bayesian model averaging (BMA) techniques to compare the performance of these forecasting approaches in short-vs. long-run horizons of S&P500 monthly excess returns. Simple averaging involves an equally-weighted averaging of the forecasts from alternative combinations of factors used in the predictive regressions, whereas BMA involves computing the predictive probability that each model is the true model and uses these predictive probabilities as weights in combing the forecasts from different models. From a given set of multiple factors, we evaluate all possible pricing models to the extent, which they describe the data as dictated by the posterior model probabilities. We find that, while simple averaging compares quite favorably to forecasts derived from a random walk model with drift (using a 10-year out-of-sample iterative period), BMA outperforms simple averaging in longer compared to shorter forecast horizons. Moreover, we find further evidence of the latter when the predictive Bayesian model includes shorter, rather than longer lags of the predictive factors. An interesting outcome of this study tends to illustrate the power of BMA in suppressing model uncertainty through model as well as parameter shrinkage, especially when applied to longer predictive horizons.     

The cyclical behavior of the Italian business survey data

This article investigates the cyclical behavior of the degree of plant utilization, inventories, order book level, and confidence climate index data (taken from Italian Business tendency surveys). It first analyzes the co-movements between the survey indicators and the Italian business cycle by performing a sensitivity analysis with respect to the reference business cycle and to the filtering technique, using time and frequency domain methods. It then discusses the ability of such indicators to predict business cycles and their importance with respect to other standard national accounts data. The results of bivariate analysis show that, whereas the degrees of plant utilization, confidence climate and order book level are procyclical, inventories appear to be countercyclical with respect to both the industrial sector and the whole-economy business cycle. Spectral analysis suggests that the high-frequency elements of the survey data tend to lead those of the business-cycle estimates obtained from the national income accounts. The choice of filtering technique affects the results, especially in the magnitude of co-movements. The forecasting exercise reveals the usefulness of such data in forecasting the real economy in the short run.     

The use of consumer and business surveys in forecasting

Surveys improve forecasting performance by adding explanatory power to a model which is based on only past values of manufacturing growth. The issue addressed in this paper is whether surveys of production expectations, when added to equations that contain lagged values of a headline index pertaining to the real economy, improve forecasting performance. If so, it may be better for researchers to use not just the headline index, but production expectations or the Economic Sentiment Indicator if they wish to better predict manufacturing growth.     

The macroeconomic effects of fiscal policy in Portugal: a Bayesian SVAR analysis

With a new quarterly dataset we estimate a Bayesian Structural Autoregression model and a Fully Simultaneous System approach to analyze the macroeconomic effects of fiscal policy. Results show that positive government spending shocks, in general, have a negative effect on real GDP; lead to “crowding-out” effects of private consumption and investment; have a persistent and positive effect on the price level and a mixed impact on the average financing cost of government debt. Explicitly considering the government debt dynamics in the model is also important. A VAR counter-factual exercise confirms that unexpected positive spending shocks create relevant “crowding-out” effects.     

Analysis on structural changes in the macroeconomic data series with the empirical evidence from China

Analysis on structural changes in macroeconomic data series has been the key issue for studying data quality. This paper studies the structural changes in China’s 36 macroeconomic time series using joint estimation model, and we find out the characteristics and movement pattern for the outliers. Our results show that most outliers show up more or less in groups, indicating that there is a significant correlation between them. The isolated outliers are not the main characteristic of China’s macroeconomic time series. Nearly all the original series contain the obvious skewness and kurtosis; hence, the hypothesis of normality is significantly rejected. Most original and outlier correction series show the non-autoregressive conditional heteroskedasticity (ARCH) characteristic, but the p value for ARCH2, ARCH4, and ARCH8 is very different. __________ Translated from Economic Research Journal (经济研究), 2005, (1) (in Chinese)     

The group method of data handling in long-range forecasting

This article focuses on the principle of self-organization in computer modeling. The forecaster introduces only a small amount of statistical data and the criteria of choice or selection of the model. The computer then determines the unique model of optimal complexity by sifting through a large number of models satisfying the given criteria. Consequently, the forecaster obtains that model which provides the most convincing prediction. Thus, the chance of the forecaster imposing his own subjectively preferred model is minimized.     

Earnings losses of displaced workers and the business cycle: An analysis with administrative data

This paper examines the earnings losses of displaced workers over the business cycle. Long-term earnings losses for these workers during a recessionary period are 1.7 to 3.9 times larger than for those observed during a period of economic growth.     

An alternative semiparametric estimate of the base-independence equivalence scale: an application to US consumer expenditure survey data

The deficit debate is a recurring theme in academic and political circles. The controversy is over the effect of deficits on inflation and interest rates. The existing body of empirical evidence does not resolve the controversy. This paper focuses on the inflationary impact of deficits. The model used is derived from a comprehensive IS-LM analysis which incorporates a foreign trade sector and a general price (adoptive expectation) adjustment mechanism. We test the model using time series data for the United states. From our results we conclude that NIA deficits have no significant bearing on the rate of inflation.     

数据挖掘技术在知识型CRM中的应用研究

企业在实施知识型CRM过程中,如果能够对海量的数据进行有效快速深入地分析和处理,就可以找出有价值的知识,能为企业做出正确的经营决策、捕捉瞬间即失的市场机会提供极大的帮助,并能从中获得丰厚的社会和经济效益。     

An international study of persistence in output: Parametric estimates using the data dependent systems approach

This paper parametrically obtains estimates of persistence in output using Pandit's (1977, 1982) Data Dependent Systems approach for modelling autoregressive and moving average processes. The estimates are based on over a century of annual data for the rate of change of output in nine industrialized countries. The sensitivity of estimates to various model selection criteria is examined. While persistence in output is found to be sensitive to model selection criteria, the output of all countries including the United States is found to have a substantial degree of persistence if the ARMA models are chosen according to the Schwarz Bayesian Criterion, but excluding the ARMA models whose moving average roots are near the unit root (which involves pile-up phenomenon). Moreover, the parametric estimates of persistence are shown not to have the known upward bias problem commonly associated with parametric estimates of persistence relative to nonparametric estimates.     

The sensitivity to key data imputations of recent estimates of income poverty and inequality in South Africa

Existing literature using South African censuses reports an increase in both poverty and inequality over the 1996 to 2001 period. This paper assesses the robustness of these results to a number of weaknesses in the personal income variable. We use a sequential regression multiple imputation approach to impute missing values and to explicitly assess the influence of implausible income values and different rules used to convert income that is measured in bands into point incomes. Overall our results for 1996 and 2001 confirm the major findings from the existing literature while generating more reliable confidence intervals for the key parameters of interest than are available elsewhere.     

跨国公司对外直接投资的区位理论及其在我国的实证

近十年来跨国公司在华的直接投资一直呈现出较快的增长,我国已连续9年成为吸收国际直接投资最多的发展中国家。但在看到总量增多的同时,我们也发现外商直接投资在我国的空间分布差异较大,这就说明区位因素对跨国公司在华的直接投资有着重大的影响。概述解释跨国公司对外直接投资的传统理论主要有海默(Hymer)的垄断优势论,巴克利(Buckley)、卡森(Carson)、拉格曼(Rugman)的内部化理论、弗农(Vernon)的产品寿命周期理论以及邓宁(Dunning)的国际生产折中理论,除了邓宁的理论将区位作为重要的子因素考虑外,这些理论的共同缺点均是只从跨国公…     

Markov chain Monte Carlo analysis of underreported count data with an application to worker absenteeism

A new approach for modeling under-reported Poisson counts is developed. The parameters of the model are estimated by Markov Chain Monte Carlo simulation. An application to workers absenteeism data from the German Socio-Economic Panel illustrates the fruitfulness of the approach. Worker absenteeism and the level of pay are unrelated, but absence rates increase with firm size.     

Demand for cigarettes in Turkey: an application of count data models

Household cigarette demand in Turkey is examined using the zero-inflated negative binomial model to account for a large portion of households not reporting cigarette smoking or purchase and estimated using the data from the national household survey implemented in 2003. Data were divided into two main groups: families with and without teenagers. Results identify relevant household head and household characteristics needed to develop effective public policy to prevent the decision to begin to smoke and to reduce cigarette purchase to lower the future growth of government healthcare expenditures. Specifically, healthcare expenditure share, income, and cigarette-price elasticities are relevant in lowering cigarette purchases. The calculated price elasticities for cigarette demand falls within the range determined by studies conducted for developed countries including the member states of the European Union. An estimate of the effect of an increase in the excise tax lowering demand is provided.     

Calculation and decomposition of income inequality in low- and middle-income countries: a survey data analysis

This article estimates income inequality in a sample of four low- and middle-income (LMI) countries namely; Albania, Nepal, Tajikistan and Tanzania using the household survey data – Nepal Living Standard Measurement Survey Second. First, we estimate the income generation function for each country and calculate the income inequality using Gini index (GI). Second, we decompose the income Gini into the determinants of income generation functions. Based on the decomposition result, socio-economic factors are the most important determinants of income inequality followed by geographic factors. Demographic factors have the least effect on income inequality in all four countries. Third, we propose a new method to quantify the effect of change in each covariate of income generation function on income Gini. That allows us to quantify the effects of change in specific policy such as increase in investment in schooling or public health to specific group of the population in society on income inequality. A carefully chosen, integrated policy can significantly reduce inequality in all four countries under study.     

Effects of income distribution in an inverse demand system: evidence from Chinese household survey data

This study provides an empirical analysis of the impact of changes in income distribution on food demand in China using data from China Health and Nutrition Survey. A new parametric form of an inverse demand system is introduced and estimated taking into account reported zero consumption. This new form is a natural extension of recent works that accommodate the incorporation of income distribution into the system and imposition of global regularity conditions in estimation. Our results generally indicate that the distribution of households across income groups is important in determining food demand in China and that a movement towards a more equal income distribution in China will stimulate the demand for vegetable, fruit, fish and eggs.     

Modeling quality demand with data from Household Budget Surveys: An application to meat and fish products in Greece

In this paper, we employ a method to examine the factors affecting quality choice by Greek households, using cross-sectional survey data. We illustrate the method using the raw data of the 2004/05 Household Budget Survey for meat and fish products. Quality elasticities of total food expenditure and household's age structure are derived. To cope with the zero expenditure problem, Heckman's two-step method is employed. Results generally suggest that several socio-economic factors affect quality demand for meat and fish.