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.     

A graduates ’ satisfaction index for the evaluation of the university overall quality

In the higher educational setting, students provide a relevant contribution to the quality of educational services. In such a context, the measurement of the perceived quality and related satisfaction for the university experience are of primary interest to evaluate the efficiency and efficacy of the learning processes. In this contribution, we aim at assessing the overall quality of the graduates’ university experience in terms of internal and external efficacy by applying the ECSI (European Customer Satisfaction Index) methodology, based on structural equation models and primarily developed in the context of customer satisfaction. For this aim, we propose a modified ECSI model tailored for the higher educational setting, explicitly taking into account the differences among groups of degree program. The study is carried out on data collected by the AlmaLaurea surveys at the University of Florence (Italy) in the period 2014–2017 and concerns a sample of more than 2,000 graduates. We find out eight latent variables that contribute to define the overall quality of university experience. These variables are differently affected by the type of degree program, with the highest levels of external efficacy observed for degree programs belonging to the educational, health, and engineering groups. It also turns out that interventions on the internal efficacy (i.e., quality of hardware and quality of humanware) have a direct positive effect on the university (i.e., loyalty) and an indirect positive effect on the society (i.e., external efficacy).     

Playing the synthesizer with Canadian data: Adding polls to a structural forecasting model

Election forecasting has become a fixture of election campaigns in a number of democracies. Structural modeling, the major approach to forecasting election results, relies on ‘fundamental’ economic and political variables to predict the incumbent’s vote share usually a few months in advance. Some political scientists contend that adding vote intention polls to these models—i.e., synthesizing ‘fundamental’ variables and polling information—can lead to important accuracy gains. In this paper, we look at the efficiency of different model specifications in predicting the Canadian federal elections from 1953 to 2015. We find that vote intention polls only allow modest accuracy gains late in the campaign. With this backdrop in mind, we then use different model specifications to make ex ante forecasts of the 2019 federal election. Our findings have a number of important implications for the forecasting discipline in Canada as they address the benefits of combining polls and ‘fundamental’ variables to predict election results; the efficiency of varying lag structures; and the issue of translating votes into seats.     

Testing of unit roots and other fractionally integrated hypotheses in the presence of structural breaks

Tests of unit roots and other nonstationary hypotheses that were proposed by Robinson (1994) are applied in this article to the Nelson and Plosser's (1982) series. The tests can be expressed in a way allowing for structural breaks under both the null and the alternative hypotheses. When applying the tests to the same dataset as in Perron (1989), we observe that our results might be consistent with those in Perron (1989) when testing the nulls of trend-stationarity or a unit-root. However, we also observe that fractionally integrated hypotheses may be plausible alternatives in the context of structural breaks at a known period of time. Final version received: August 2000/Final version accepted: August 2001 RID="*" ID="*"  The author gratefully acknowledges the financial support from the European TMR grant No. ERBFMRX-CT-98-0213. Comments of two anonymous referees are also acknowledged.     

Central Bank's interventions and the Fisher hypothesis: a threshold cointegration investigation

The long-run relationship between nominal interest rates and inflation is examined, allowing for structural breaks and asymmetric mean reversion. From a Threshold AutoRegressive (TAR) test applied to the residuals of the cointegration relationship (while allowing for both a break in the mean of the long-run equation and a smooth regime-transition), there is strong evidence for non-linear mean reversion properties for the real interest rates of the US Treasury Bill market. This suggests asymmetric changes to inflation shocks in the Central Bank's reaction function. The existence of different regimes is consistent with some interpretations of the monetary policies run by the Fed, such as credibility and opportunism.     

Carbon Taxes and Joint Implementation. An Applied General Equilibrium Analysis for Germany and India

Germany has committed itself toreducing its carbon emissions by 25 percent in2005 as compared to 1990 emission levels. Toachieve this goal, the government has recentlylaunched an environmental tax reform whichentails a continuous increase in energy taxesin conjunction with a revenue-neutral cut innon-wage labor costs. This policy is supposedto yield a double dividend, reducing both, theproblem of global warming and high unemploymentrates. In addition to domestic actions,international treaties on climate protectionallow for the supplementary use of flexibleinstruments to exploit cheaper emissionreduction possibilities elsewhere. One concreteoption for Germany would be to enter jointimplementation (JI) with developing countriessuch as India where Germany pays emissionreduction abroad rather than meeting itsreduction target solely by domestic action. Inthis paper, we investigate whether anenvironmental tax reform cum JI providesemployment and overall efficiency gains ascompared to an environmental tax reformstand-alone. We address this question in theframework of a large-scale general equilibriummodel for Germany and India where Germany mayundertake JI with the Indian electricitysector. Our main finding is that JI offsetslargely the adverse effects of carbon emissionconstraints on the German economy. JIsignificantly lowers the level of carbon taxesand thus reduces the total costs of abatementas well as negative effects on labor demand. Inaddition, JI triggers direct investment demandfor energy efficient power plants produced inGermany. This provides positive employmenteffects and additional income for Germany. ForIndia, joint implementation equips itselectricity industry with scarce capital goodsleading to a more efficient power productionwith lower electricity prices for the economyand substantial welfare gains.     

The proper panel econometric specification of the gravity equation: A three-way model with bilateral interaction effects

We argue that the proper specification of a panel gravity model should include main (exporter, importer, and time) as well as time invariant exporter-by-importer (bilateral) interaction effects. In a panel of 11 APEC countries, the latter are highly significant and account for the largest part of variation. First version received: February 2001/Final version received: June 2002 RID="*" ID="*"  We are grateful to two anonymous referees and Robert Kunst for their helpful comments.     

Modeling Disinterest and Dislike: A Bounded Bayesian Mixed Logit Model of the UK Market for GM Food

Mixed logit models represent a powerful discrete choice analytical model but require assumptions about the functional form of the parameter distributions. The use of unbounded distributions, such as the normal distribution, may be regarded as unsuitable where theory indicates that all are negatively affected by increases in an attribute, such as price. Bounded distributions such as the triangular and log-normal are unable to model the case where a section of the population is indifferent towards an attribute, while the remainder are negatively disposed toward it. Train and Sonnier’s bounded mixed logit model accommodates these features and is employed in this paper. A censored normal and Johnson’s S_b distribution are used to model preferences in the UK for food attributes, including price and GM technology. Bi-modal distributions are identified regarding GM food: some are unlikely to ever consume it, some are close to indifference and willing to consume at relatively small discounts while the remainder are fairly unresponsive to further price reductions.     

数据拟合回归方法的探讨

建立回归方程进行分析预测,大多采用人们熟知的"最小二乘法"。但是"最小二乘法"有本质上的一个弱点,由于系数矩阵的病态性质:系数矩阵中的最大值相对很大,系数矩阵的行列式值相对较小,在求解方程时,系数中的微小变化可能导致结果不稳定,预测效果不佳甚至失真。本文另辟蹊径,与"最小二乘法"的拟合原则不同,我们是最小化误差绝对值中的最大值。该法克服了"最小二乘法"有时不稳定的缺陷,继而提高拟合精度,使预测效果更精确。