A look into the factor model black box: Publication lags and the role of hard and soft data in forecasting GDP

We derive forecast weights and uncertainty measures for assessing the roles of individual series in a dynamic factor model (DFM) for forecasting the euro area GDP from monthly indicators. The use of the Kalman smoother allows us to deal with publication lags when calculating the above measures. We find that surveys and financial data contain important information for the GDP forecasts beyond the monthly real activity measures. However, this is discovered only if their more timely publication is taken into account properly. Differences in publication lags play a very important role and should be considered in forecast evaluation.     

Forecasting monthly and quarterly time series using STL decomposition

This paper is a re-examination of the benefits and limitations of decomposition and combination techniques in the area of forecasting, and also a contribution to the field, offering a new forecasting method. The new method is based on the disaggregation of time series components through the STL decomposition procedure, the extrapolation of linear combinations of the disaggregated sub-series, and the reaggregation of the extrapolations to obtain estimates for the global series. Applying the forecasting method to data from the NN3 and M1 Competition series, the results suggest that it can perform well relative to four other standard statistical techniques from the literature, namely the ARIMA, Theta, Holt-Winters’ and Holt’s Damped Trend methods. The relative advantages of the new method are then investigated further relative to a simple combination of the four statistical methods and a Classical Decomposition forecasting method. The strength of the method lies in its ability to predict long lead times with relatively high levels of accuracy, and to perform consistently well for a wide range of time series, irrespective of the characteristics, underlying structure and level of noise of the data.     

新形势下企业经济管理的绿色发展模式研究

本文主要针对企业在新形势下的经济管理应当建立起一个绿色生态模式进行探讨,并深入分析当前形势下的企业经济管理绿色模式对于企业在可持续发展中所起到的作用。     

LOD技术在三维地形图实时可视化中的应用研究

随着计算机科学、计算机图形学和现代测绘科学的迅速发展,三维数字地形图的研究与实现越来越成为人们研究和关注的热点,要实现三维地形图的实时可视化,应用LOD技术的研究又是非常必要的,如何针对大数据量三维地形图建立不同细节层次的模型和优化其算法又成为要研究关键技术。本文重点对LOD技术的原理、分类和应用进行比较与探讨。     

Blocked-Error-R 2: A Conceptually Improved Definition of the Proportion of Explained Variance in Models Containing Loops or Correlated Residuals

Bentler and Raykov (2000, Journal of Applied Psychology 85: 125–131), and Jöreskog (1999a, http://www.ssicentral.com/lisrel/column3.htm, 1999b http://www.ssicentral. com/lisrel/column5.htm) proposed procedures for calculating R ² for dependent variables involved in loops or possessing correlated errors. This article demonstrates that Bentler and Raykov’s procedure can not be routinely interpreted as a “proportion” of explained variance, while Jöreskog’s reduced-form calculation is unnecessarily restrictive. The new blocked-error-R ² (beR ²) uses a minimal hypothetical causal intervention to resolve the variance-partitioning ambiguities created by loops and correlated errors. Hayduk (1996) discussed how stabilising feedback models – models capable of counteracting external perturbations – can result in an acceptable error variance which exceeds the variance of the dependent variable to which that error is attached. For variables included within loops, whether stabilising or not, beR ² provides the same value as Hayduk’s (1996) loop-adjusted-R ². For variables not involved in loops and not displaying correlated residuals, beR ² reports the same value as the traditional regression R ². Thus, beR ² provides a conceptualisation of the proportion of explained variance that spans both recursive and nonrecursive structural equation models. A procedure for calculating beR ² in any SEM program is provided.     

Unemployment duration and the interactions between unemployment insurance and social assistance

Existing studies suggest that reforms that reduce the generosity of the unemployment benefits should lower unemployment. Despite the large number of such reforms implemented in Europe in the past decades, evidence from various data sources shows very little correlation with the evolution of unemployment. This paper suggests that the scant success of these labour market reforms can be explained by the interactions between unemployment insurance and other social assistance programmes. Evidence from the European Community Household Panel shows that recipients of unemployment insurance who are also eligible for other welfare schemes are indeed less sensitive to changes in the level and the duration of their benefits.     

Value and liquidity under changing market conditions

Papers studying the liquidity of a market tend to focus on decisions involving the trade-off between the selling price and the time-till-sale for a given set of market conditions. This paper characterizes market conditions using a price-probability locus; a change in market conditions is some combination of changes in the level and/or slope of this locus. I show how the effect of either type of change on price and on the probability-of-sale can be decomposed into those commonly associated with an increase in the value and those which involve a substitution between price and probability. Two adding-up conditions restrict the set of possible predictions. Though the discussion focusses on real estate market, where scarcity is rationed by a mechanism which combines search and bargaining, the same ideas apply to markets with other types of selling mechanisms.     

Efficient learning via simulation: A marginalized resample-move approach

In state–space models, parameter learning is practically difficult and is still an open issue. This paper proposes an efficient simulation-based parameter learning method. First, the approach breaks up the interdependence of the hidden states and the static parameters by marginalizing out the states using a particle filter. Second, it applies a Bayesian resample-move approach to this marginalized system. The methodology is generic and needs little design effort. Different from batch estimation methods, it provides posterior quantities necessary for full sequential inference and recursive model monitoring. The algorithm is implemented both on simulated data in a linear Gaussian model for illustration and comparison and on real data in a Lévy jump stochastic volatility model and a structural credit risk model.     

Is econometrics useful for private policy making? A case study of replacement policy at an auto rental company

The goal of this paper is to illustrate the potential usefulness of econometrics as a tool to assist private policy makers. We provide a case study and detailed econometric analysis of the automobile replacement policy adopted by a large car rental company. Unlike public policy making–where the benefits from using econometric models and “science-based” approaches to policy making are hard to quantify because the outcomes of interest are typically subjective quantities such as “social welfare”–in the case of firms there is an objective, easily quantifiable criterion for judging whether policy A is better than policy B: profits. We introduce and estimate an econometric model of the rental histories of individual cars in the company’s fleet. Via stochastic simulations, we show that the model provides a good approximation to the company’s actual operations. In particular, the econometric model is able to reproduce the extraordinarily high rates of return that the company obtains on its rental cars, with average internal rates of return between purchase and sale of approximately 50%. However, the econometric model can simulate outcomes under a range of counterfactual vehicle replacement policies. We use the econometric model to simulate the profitability of an alternative replacement policy under pessimistic assumptions about the rate maintenance costs would increase and rental rates would have to be decreased if the company were to keep its rental cars longer than it does under the status quo. Depending on the vehicle type, we find that the company’s expected discounted profits would be between 6% to over 140% higher under the suggested alternative operating strategy where vehicles are kept longer and rental rates of older vehicles are discounted to induce customers to rent them. The company found this analysis to be sufficiently convincing that it undertook an experiment to verify the predictions of the econometric model.     

Propensity to firm creation: empirical research using structural equations

The identification of the entrepreneurs’ characteristics and the knowledge of the entrepreneurial profile of university students have been assuming a growing importance in the development of educational programs directed towards the entrepreneurship and start-up processes. This study aims to identify the factors that most contribute for the intention to start up a business. The research also tries to identify the profile of a potential entrepreneur student concerning several characteristics: personal attributes, family, demographic variables and motivations. Research findings include the idea that entrepreneurship education is the most relevant factor in what concerns the propensity to business creation. On the other side, personal characteristics have an important role in shaping motivation to start-up a business and perceived hurdles have a negative impact in the intention to start-up. The results may be relevant when developing an adequate educational program directed to the entrepreneurship education and start-up processes.