What accounts for the changes in U.S. fiscal policy transmission?

Using vector autoregressions on U.S. time series for 1957-1979 and 1983-2004, we find government spending shocks to have stronger effects on output, consumption, and wages in the earlier sample. We try to account for this observation within a DSGE model featuring price rigidities and limited asset market participation. Specifically, we estimate the structural parameters of the model for both samples by matching impulse responses. Model-based counterfactual experiments suggest that increased asset market participation accounts for some of the changes in fiscal transmission. However, the key quantitative factor appears to be the more active monetary policy of the Volcker-Greenspan period. JEL Classification: E21, E62, E63Asset Market Participation, DSGE, Fiscal Policy, government spending, Minimum Distance Estimation, monetary policy, Vector autoregression

Classroom Games in Economics : A Quantitative Assessment of the `Beer Game'

Using an experiment, I compare the use of the `Beer Distribution' classroom game with the more traditional `chalk and talk' approach to teach students about inventories and the macroeconomy. My empirical results confirm and extend our understanding of the relative strengths and weaknesses of the use of classroom games : the game tends to improve interest and motivation on average, though some students dislike their use ; the game is e ective at driving home its key messages, but it may wrongly lead students to disregard other important factors ; the game is inferior where facts mastery or definitional learning is required. Rather than an endorsement or a criticism of classroom games, the conclusion is cautionary advice on how to best make use of games within an overall course. Key words: Classroom experiments and games ; motivation ; student learning outcomes JEL classification: A22 ; C90

Monetary policy analysis in a small open economy using Bayesian cointegrated structural VARs

Structural VARs have been extensively used in empirical macroeconomics during the last two decades, particularly in analyses of monetary policy. Existing Bayesian procedures for structural VARs are at best confined to a severly limited handling of cointegration restrictions. This paper extends the Bayesian analysis of structural VARs to cover cointegrated processes with an arbitrary number of cointegrating relations and general linear restrictions on the cointegration space. A reference prior distribution with an optional small open economy effect is proposed and a Gibbs sampler is derived for a straightforward evaluation of the posterior distribution. The methods are used to analyze the effects of monetary policy in Sweden. JEL Classification: C11, C32, E52Counterfactual experiments, Impulse responses, monetary policy, Structural, Vector autoregression

Weak and strong cross section dependence and estimation of large panels

This paper introduces the concepts of time-specific weak and strong cross section dependence. A double- indexed process is said to be cross sectionally weakly dependent at a given point in time, t, if its weighted average along the cross section dimension (N) converges to its expectation in quadratic mean, as N is increased without bounds for all weights that satisfy certain ‘granularity’ conditions. Relationship with the notions of weak and strong common factors is investigated and an application to the estimation of panel data models with an infinite number of weak factors and a finite number of strong factors is also considered. The paper concludes with a set of Monte Carlo experiments where the small sample properties of estimators based on principal components and CCE estimators are investigated and compared under various assumptions on the nature of the unobserved common effects. JEL Classification: C10, C31, C33Panels, Strong and Weak Cross Section Dependence, Weak and Strong Factors

Using mean reversion as a measure of persistence

This paper elaborates on the alternative measure of persistence recently suggested in Marques (2004), which is based on the idea of mean reversion. A formal distinction between the “unconditional probability of a given process not crossing its mean in period t” and its estimator, is made clear and the relationship between this new measure and the widely used “sum of the autoregressive coefficients”, as alternative measures of persistence, is investigated. Using the law of large numbers and the central limit theorem, properties for the estimator of the new measure of persistence are established, which allow tests of hypotheses to be performed, under very general conditions. Finally, some Monte Carlo experiments are conducted in order to compare the finite sample properties of the estimator for the “unconditional probability of a given process not crossing its mean in period t” and the OLS estimator for the “sum of the autoregressive coefficients”. JEL Classification: E31, C22, E52Inflation persistence, Mean reversion, non-parametric estimator

Infinite-dimensional VARs and factor models

This paper introduces a novel approach for dealing with the 'curse of dimensionality' in the case of large linear dynamic systems. Restrictions on the coefficients of an unrestricted VAR are proposed that are binding only in a limit as the number of endogenous variables tends to infinity. It is shown that under such restrictions, an infinite-dimensional VAR (or IVAR) can be arbitrarily well characterized by a large number of finite-dimensional models in the spirit of the global VAR model proposed in Pesaran et al. (JBES, 2004). The paper also considers IVAR models with dominant individual units and shows that this will lead to a dynamic factor model with the dominant unit acting as the factor. The problems of estimation and inference in a stationary IVAR with unknown number of unobserved common factors are also investigated. A cross section augmented least squares estimator is proposed and its asymptotic distribution is derived. Satisfactory small sample properties are documented by Monte Carlo experiments. JEL Classification: C10, C33, C51Large N and T Panels, Factor models, Global VAR, VAR, Weak and Strong Cross Section Dependence

Is the New Keynesian Phillips curve flat?

Macroeconomic data suggest that the New Keynesian Phillips curve is quite flat - despite microeconomic evidence implying frequent price adjustments. While real rigidities may help to account for the conflicting evidence, we propose an alternative explanation: if price markup/cost-push shocks are persistent and negatively correlated with the labor share, the latter being a widely used measure for marginal costs, the estimated pass-through of measured marginal costs into inflation is limited, even if prices are fairly flexible. Using a standard New Keynesian model, we show that the GMM approach to the New Keynesian Phillips curve leads to inconsistent and upward biased estimates if cost-push shocks indeed are persistent. Monte Carlo experiments suggest that the bias is quite sizeable: we find average price durations estimated as high as 12 quarters, when the true value is about 2 quarters. Moreover, alternative estimators appear to be biased as well, while standard diagnostic tests fail to signal a misspecification of the model. JEL Classification: E30, C15Cost-push shocks, GMM estimation, New Keynesian Phillips curve, Price Rigidities

Econometric analysis of high dimensional VARs featuring a dominant unit

This paper extends the analysis of infinite dimensional vector autoregressive models (IVAR) proposed in Chudik and Pesaran (2010) to the case where one of the variables or the cross section units in the IVAR model is dominant or pervasive. This extension is not straightforward and involves several technical difficulties. The dominant unit influences the rest of the variables in the IVAR model both directly and indirectly, and its effects do not vanish even as the dimension of the model (N) tends to infinity. The dominant unit acts as a dynamic factor in the regressions of the non-dominant units and yields an infinite order distributed lag relationship between the two types of units. Despite this it is shown that the effects of the dominant unit as well as those of the neighborhood units can be consistently estimated by running augmented least squares regressions that include distributed lag functions of the dominant unit. The asymptotic distribution of the estimators is derived and their small sample properties investigated by means of Monte Carlo experiments. JEL Classification: C10, C33, C51Dominant Units, Factor models, IVAR Models, Large Panels, Weak and Strong Cross Section Dependence

Automated design analysis, assembly planning and motion study analysis using immersive virtual reality

Previous research work at Heriot-Watt University using immersive virtual reality (VR) for cable harness design showed that VR provided substantial productivity gains over traditional computer-aided design (CAD) systems. This follow-on work was aimed at understanding the degree to which aspects of this technology were contributed to these benefits and to determine if engineering design and planning processes could be analysed in detail by nonintrusively monitoring and logging engineering tasks. This involved using a CAD-equivalent VR system for cable harness routing design, harness assembly and installation planning that can be functionally evaluated using a set of creative design-tasks to measure the system and users' performance. A novel design task categorisation scheme was created and formalised which broke down the cable harness design process and associated activities. The system was also used to demonstrate the automatic generation of usable bulkhead connector, cable harness assembly and cable harness installation plans from non-intrusive user logging. Finally, the data generated from the user-logging allowed the automated activity categorisation of the user actions, automated generation of process flow diagrams and chronocyclegraphs