Can stable environmental protection officials’ tenure reduce illegal emissions?

Based on the day-night PM_2.5 difference of the nearest atmospheric monitoring points to measure whether there is illegal emission, this paper explores the impact of environmental protection officials' tenure (EPLT) on illegal emissions. The results show that there is a positive correlation between EPLT and illegal emissions. Stable EPLT can reduce illegal emissions by increasing environmental information disclosure and environmental subsidies. It can increase illegal emissions by weakening public pollution reporting and media supervision, environmental law enforcement and promoting corruption. In addition, EPLT can increase illegal emissions as EPLT is less than 3.55 years, while EPLT can increase illegal emissions as EPLT exceeds 6.21 years. Further, when mayor's tenure and EPLT are both stable, the promotion effect of EPLT on illegal emission is stronger. Stable company director's tenure can also aggravate the promotion effect of EPLT on illegal emissions.     

Forecasting economic time series using flexible versus fixed specification and linear versus nonlinear econometric models

Nine macroeconomic variables are forecast in a real-time scenario using a variety of flexible specification, fixed specification, linear, and nonlinear econometric models. All models are allowed to evolve through time, and our analysis focuses on model selection and performance. In the context of real-time forecasts, flexible specification models (including linear autoregressive models with exogenous variables and nonlinear artificial neural networks) appear to offer a useful and viable alternative to less flexible fixed specification linear models for a subset of the economic variables which we examine, particularly at forecast horizons greater than 1-step ahead. We speculate that one reason for this result is that the economy is evolving (rather slowly) over time. This feature cannot easily be captured by fixed specification linear models, however, and manifests itself in the form of evolving coefficient estimates. We also provide additional evidence supporting the claim that models which ‘win’ based on one model selection criterion (say a squared error measure) do not necessarily win when an alternative selection criterion is used (say a confusion rate measure), thus highlighting the importance of the particular cost function which is used by forecasters and ‘end-users’ to evaluate their models. A wide variety of different model selection criteria and statistical tests are used to illustrate our findings.     

A network experiment in continuous time: The influence of link costs

In recent work on non-cooperative network formation star-shaped networks play an important role. In a particular theoretical model of Bala and Goyal (2000) center-sponsored stars are the only strict Nash networks. In testing this theoretical model, Falk and Kosfeld (2003) do not find experimental evidence that players select the center-sponsored star. Based on a slight modification of Bala and Goyal’s model, we design a network formation experiment in which, depending on link costs, periphery-sponsored stars and the empty network are the only strict Nash networks. We observe that almost all groups not only reach a strict Nash network once but also switch the center player in periphery-sponsored stars several times. The main innovation in our experiment is to use a continuous time framework which we believe to be a more realistic setting to study behavior in network formation situations and which makes coordination on stars much easier than simultaneous strategy adaptation in discrete time. Electronic Supplementary Material Supplementary material is available in the online version of this article at http://dx.doi.org/10.1007/s10683-006-9125-1. JEL Classification C72 · C92 · D81     

DSGE forecasts of the lost recovery

The years following the Great Recession were challenging for forecasters. Unlike other deep downturns, this recession was not followed by a swift recovery, but instead generated a sizable and persistent output gap that was not accompanied by deflation as a traditional Phillips curve relationship would have predicted. Moreover, the zero lower bound and unconventional monetary policy generated an unprecedented policy environment. We document the actual real-time forecasting performance of the New York Fed dynamic stochastic general equilibrium (DSGE) model during this period and explain the results using the pseudo real-time forecasting performance results from a battery of DSGE models. We find the New York Fed DSGE model’s forecasting accuracy to be comparable to that of private forecasters, and notably better for output growth than the median forecasts from the FOMC’s Summary of Economic Projections. The model’s financial frictions were key in obtaining these results, as they implied a slow recovery following the financial crisis.     

Data revisions to German national accounts: Are initial releases good nowcasts?

Data revisions to national accounts pose a serious challenge to policy decision making. Well-behaved revisions should be unbiased, small, and unpredictable. This article shows that revisions to German national accounts are biased, large, and predictable. Moreover, with use of filtering techniques designed to process data subject to revisions, the real-time forecasting performance of initial releases can be increased by up to 23%. For total real GDP growth, however, the initial release is an optimal forecast. Yet, given the results for disaggregated variables, the averaging out of biases and inefficiencies at the aggregate GDP level appears to be good luck rather than good forecasting.     

通货膨胀实时预测及菲利普斯曲线的适用性

本文从实时分析的视角,基于多种退势方法的产出缺口最终估计、准最终估计和实时估计序列,分别构建了四类预测模型对我国通货膨胀率进行预测,分析了产出缺口修正效应和滞后阶数变化效应对通胀预测的影响,并进一步考察了产出缺口在通胀预测中的作用及菲利普斯曲线在通胀预测中的适用性。研究结论表明,通胀率的实时预测效果要明显比基于最终数据的差,其中滞后阶数变化效应对实时预测精度的影响大于产出缺口修正效应;尤为重要的是,尽管在最终数据的预测分析中,产出缺口的引入能够提高通胀率的预测精度,但是在实时预测中,产出缺口没有提供有价值的信息,因此"产出—通胀"型菲利普斯曲线在我国通胀实时预测中并不适用。     

Professional forecasters and real-time forecasting with a DSGE model

This paper analyses the real-time forecasting performance of the New Keynesian DSGE model of Galí, Smets and Wouters (2012), estimated on euro area data. It investigates the extent to which the inclusion of forecasts of inflation, GDP growth and unemployment by professional forecasters improve the forecasting performance. We consider two approaches for conditioning on such information. Under the “noise” approach, the mean professional forecasts are assumed to be noisy indicators of the rational expectations forecasts implied by the DSGE model. Under the “news” approach, it is assumed that the forecasts reveal the presence of expected future structural shocks in line with those estimated in the past. The forecasts of the DSGE model are compared with those from a Bayesian VAR model, an AR(1) model, a sample mean and a random walk.     

利用现场可编程门阵列FPGA开发专用实时图像处理系统芯片

本文介绍了一个实时图像处理系统中，利用ＦＰＧＡ开发专用算法模块的范例，使人 ＦＰＧＡ的应用方法有一个较完整的认识。     

实时数据与货币政策分析和评价——基于产出缺口的一个说明

本文基于1994Q1-2008Q4的数据并分别利用三次趋势和HP滤波两种模型方法估计了我国的实时、准实时和最终产出缺口,分析表明,这一时期我国的产出缺口遭受了较大而且高度持续的修正,说明我国的实时产出缺口和基于事后修正数据估计的产出缺口有很大不同。由于产出缺口是货币政策决策的重要依据,而货币政策决策总发生在实时,不能等待后来产出缺口等数据信息的修正,因此,区分实时数据和事后修正数据对政策分析和评价而言可能就十分重要。     

Incorporating vintage differences and forecasts into Markov switching models

This paper incorporates vintage differences and forecasts into the Markov switching models described by Hamilton (1994). The vintage differences and forecasts induce parameter breaks close to the end of the sample, too close for standard maximum likelihood techniques to produce precise parameter estimates. A supplementary procedure estimates the statistical properties of the end-of-sample observations that behave differently from the rest, allowing inferred probabilities to reflect the breaks. Empirical results using real-time data show that these techniques improve the ability of a Markov switching model based on GDP and GDI to recognize the start of the 2001 recession.