The Taylor principle in a medium-scale macroeconomic model

We consider a medium-scale New-Keynesian model which combines features that have been shown to explain fairly well postwar U.S. business cycles. Our main result demonstrates that the determinacy properties of forward-looking interest rate rules resemble, at least qualitatively, the corresponding outcomes under current-looking rules. We explain how and why the empiri-cally relevant features of our model generate this novel result.     

Patterns of ‘Mock Bureaucracy’ in Mining Disasters: An Analysis of the Westray Coal Mine Explosion

Recent studies on the antecedents of industrial crises have tended to focus on disasters in high-risk systems involving complex technologies and tightly-knit processes. This paper examines events leading up to mining disasters which past research has characterized as being typically more foreseeable and avoidable. We discuss how many mining disasters are likely to be the result of ‘mock bureaucracies’ or situations characterized by overt violation of safety rules at the workplace. Using the Westray mine explosion as an illustrative case, the paper traces the development and institutionalization of a mock bureaucracy in an organization. Implications for further research and understanding of industrial crises are drawn.     

Research orientation and agglomeration: Can every region become a Silicon Valley?

Not only success stories, such as Silicon Valley, but also non-success stories can inform regional innovation policy. In order to provide a benchmark for regional innovation systems we compare both success and non-success stories. Regional innovation systems differ in structural and functional requirements, because development processes are path dependent. We suggest that regions’ development paths emerge from agglomeration patterns and research orientation. Accordingly, we have developed a typology of regions including (1) their agglomeration patterns (either MAR or Jacobs’ type) and (2) the degree to which their research is predominantly oriented towards obtaining fundamental understanding or addressing considerations of use. We combine qualitative and quantitative data on thirty-six European regions to categorize them according to research orientation and agglomeration, thereby developing a typology. We use this typology and some basic quantitative economic data to see how success and non-success regions are distributed. Our results indicate that a better understanding of how to combine agglomeration patterns with research orientation can guide context-sensitive policy.     

Learning about fiscal policy and the effects of policy uncertainty

In this paper we ask how uncertainty about fiscal policy affects the impact of fiscal policy changes on the economy when the government tries to counteract a deep recession. The agents in our model are uncertain about the conduct of fiscal policy and act as econometricians by estimating fiscal policy rules that might change over time.We find that assuming that agents are not instantaneously aware of the new fiscal policy regime in place leads to substantially more volatility in the short run and persistent differences in average outcomes. We highlight issues that can arise when a policymaker wants to announce a policy change. From a methodological perspective, we introduce a novel way to model learning in the face of discrete policy changes.     

Fiscal News, State Budget Rules, and Tax-Exempt Bond Yields

This paper investigates how state fiscal institutions such as balanced-budget rules and restrictions on state debt issuance mediate the bond market reaction to state fiscal news. We analyze data on the yields of bonds issued by different states, as reported in the “Chubb Relative Value Survey,” along with data on state budget forecasts for the period 1988–1998. We find that unexpected deficits are correlated with higher state bond yields. This effect is smaller for states with tight antideficit rules than for states without these fiscal rules. Unexpected deficits have a particularly large effect in raising bond yields of states with tax limits. These results suggest that bond market participants view fiscal institutions as relevant in assessing the risk characteristics of tax-exempt bonds and that the economic significance of these institutions depends on the state's economic and fiscal circumstances.     

Nested analysis of variance: Review of methods

Summary Methods of the nested analysis of variance procedures are discussed and a formalized three-way nested model is outlined. A summary of the statistical tests for the assumptions relevant to the model is given together with an outline of the numerical methods for calculating the sum of squares, the degrees of freedom, the mean squares, the tests of significance, and the estimate of variance components. Several methods are given for obtaining confidence limits for variance components. Procedures are presented for utilizing the variance components to estimate process and/or control limits and to obtain the most efficient or optimum sampling scheme. Some differences between the nested analysis of variance model and the crossed analysis of variance model are explained.     

Exact likelihood computation for nonlinear DSGE models with heteroskedastic innovations

Phenomena such as the Great Moderation have increased the attention of macroeconomists towards models where shock processes are not (log-)normal. This paper studies a class of discrete-time rational expectations models where the variance of exogenous innovations is subject to stochastic regime shifts. We first show that, up to a second-order approximation using perturbation methods, regime switching in the variances has an impact only on the intercept coefficients of the decision rules. We then demonstrate how to derive the exact model likelihood for the second-order approximation of the solution when there are as many shocks as observable variables. We illustrate the applicability of the proposed solution and estimation methods in the case of a small DSGE model.     

ARTHUR M. OKUN: ECONOMICS FOR POLICYMAKING

Abstract. This is a study of macroeconomics in action: how an applied macroeconomist works in a policy context to provide analysis and guidance on specific issues of public concern. We examine and classify Arthur Okun's policy essays, and thereby try to gain a better understanding of the role of economists in the policy-making process.     

Monitoring the mean and the variance of a stationary process

We deal with the problem of how deviations in the mean or the variance of a time series can be detected. Several simultaneous control charts are introduced which are based on EWMA (exponentially weighted moving average) statistics for the mean and the empirical variance. The combined X − S² EWMA chart is extended to time series. Further simultaneous charts are considered. The comparision of these schemes shows that the residual attempt must be favored if a variance change is present.     

Irregular workloads with MRP systems: Some causes and consequences

Material Requirements Planning (MRP) systems have been widely applied in industry to better manage multiproduct, multistage production environments. Although many applications have been quite successful, much is still left to the planner's intuition as to how to assure that master schedules, component lot sizes, and priorities realistically conform to the capacity limits at individual work centers. Capacity issues may indeed be the soft spot in MRP logic.This paper explores some possible causes of irregular workload patterns when using an MRP system. Better insight on which factors cause temporary bottlenecks could help managers better assess the vulnerability of their plants to this problem. It might also suggest ways of dampening peaks and valleys. The problem setting is a multistage environment; several products are made from various subassemblies and parts. Each shop order is routed through one or more capacitated work centers. An order is delayed either by temporary capacity shortages or the unavailability of components. Of course, the second delay can be caused by capacity problems previously encountered by the shop orders of its components.Seven experimental factors are tested with a large-scale simulator, and five performance measures are analyzed. The factors are the number of levels in the bill of material, the average load on the shop, the average lot size, the choice of priority rule, demand variability, the use of a gateway department, and the degree of equipment specialization. We have one measure of customer service, two for inventory, and two for workload. The workload measures are unconventional, since our interest is when workload variability occurs and how it affects inventory and customer service.The simulator has been developed over the course of eight years, and since this study has been further enhanced to handle many more factors. The simulator was validated recently with real data at two manufacturing plants. It is quite general, in that the bills of material, shop configuration, routings, worker efficiencies, and operating rules can be changed as desired.An initial screening experiment was performed, whereupon the average load and priority rules were not statistically significant at even the .05 level. A full factorial analysis with two replications was then conducted on the five remaining factors. Multivariate analysis of variance (MANOVA) and analysis of variance (ANOVA) statistical tests have been performed.The results confirm that workload variability can have a detrimental impact on customer service and inventory. The following structural changes to the manufacturing system can be beneficial, but tend to be more difficult to achieve. More BOM levels improve customer service, but increase inventory and capacity bottlenecks. Resource flexibility is a powerful tool to reduce workload variability. Capacity slack averaging much over 10% is wasteful, having no benefits for inventory and customer service. In general, revising the routing patterns only, such as creating more dominant paths, will not give big payoffs. The following procedural changes are easier to implement. Master schedules which smooth aggregate resources are an excellent device to reduce workload variability. Even with a smooth MPS, debilitating workload variability can still occur due to the design of the BOM, lot size, and leadtime offset parameters. Selecting a priority rule does not seem to be of overriding importance compared to master scheduling and component lot sizing. These findings must be considered within the context of the range of plant environments encompassed by this study.     

Regional output growth in the United Kingdom: More timely and higher frequency estimates from 1970

Output growth estimates for regions of the UK are currently published at an annual frequency only, released with a long delay, and offer limited historical coverage. To improve the regional database this paper develops a mixed-frequency multivariate model and uses it to produce consistent estimates of quarterly regional output growth dating back to 1970. We describe how these estimates are updated and evaluated on an ongoing, quarterly basis to publish online (at www.escoe.ac.uk/regionalnowcasting ) more timely regional growth estimates. We illustrate how the new quarterly data can contribute to our historical understanding of business cycle dynamics and connectedness between regions.     

Playing with the Rules of the Game: Social Innovation for Urban Transformation

Innovation is perhaps the buzzword in local economic development policy. Associated narrowly with neoliberal ideas, conventional notions of innovation—like its capitalocentric counterparts, enterprise and entrepreneurialism—may promise higher productivity, global competitiveness and technological progress but do not fundamentally change the ‘rules of the game’. In contrast, an emerging field reimagines social innovation as disruptive change in social relations and institutional configurations. This article explores the conceptual and political differences within this pre‐paradigmatic field, and argues for a more transformative understanding of social innovation. Building on the work of David Graeber, I mobilize the novel constructs of ‘play’ and ‘games’ to advance our understanding of the contradictory process of institutionalizing social innovation for urban transformation. This is illustrated through a case study of Liverpool, where diverse approaches to innovation are employed in attempts to resolve longstanding socio‐economic problems. Dominant market‐ and state‐led economic development policies—likened to a ‘regeneration game’—are contrasted with more experimental, creative, democratic and potentially more effective forms of social innovation, seeking urban change through playing with the rules of the game. I conclude by considering how the play–game dialectic illuminates and reframes the way transformative social innovation might be cultivated by urban policy, the contradictions this entails, and possible ways forward.     

Unpacking the evolving process of pay-for-performance system implementation

Compensation researchers and practitioners often wrestle with issues of how organizations manage pay-for-performance (PFP) systems. Research has mostly addressed employee work outcomes of pay practices and has largely considered the PFP system as a static mechanism. We build a cyclical process model of how PFP systems are enacted, transformed, and managed in firms, ultimately providing a theoretical basis for enhancing the understanding of PFP system design and effectiveness. Drawing upon agency theory, cybernetic theory, and Bowen and Ostroff (2004)’s HRM system strength approach, our model identifies critical factors—PFP system formalization, PFP distinctiveness, PFP consistency, and PFP consensus —that influence control over PFP system implementation in organizations. In particular, our model addresses the critical role of managers in implementing and synthesizing PFP systems, which ultimately influences the design of PFP systems over time. Our model explains how the misalignment of espoused and enacted PFP practices is created and resolved in organizations.     

Learning about monetary policy rules when the cost-channel matters

We study how monetary policy may affect determinacy and expectational stability (E-stability) of rational expectations equilibrium when the cost channel of monetary policy matters. Focusing on instrumental Taylor-type rules and optimal target rules, we show that standard policies can induce indeterminacy and expectational instability when the cost channel is present. A naïve application of the traditional Taylor principle could be misleading, and expectations-based reaction function under discretion does not always induce determinate and E-stable equilibrium. This result contrasts with the findings of Bullard and Mitra [2002. Learning about monetary policy rules. Journal of Monetary Economics 49, 1105–1129] and Evans and Honkapohja [2003. Expectations and stability problem for optimal monetary policies. Review of Economic Studies 70, 807–824] for the standard new Keynesian model. The ability of the central bank to commit to an optimal policy is an antidote to these problems.     

Optimal interest-rate rules and inflation stabilization versus price-level stabilization

This paper compares the properties of interest-rate rules such as simple Taylor rules and rules that respond to price-level fluctuations (called Wicksellian rules) in a basic forward-looking model. By introducing appropriate history dependence in policy, Wicksellian rules perform better than optimal Taylor rules in terms of welfare, robustness to alternative shock processes, and are less prone to equilibrium indeterminacy. A simple Wicksellian rule augmented with a high degree of interest rate inertia resembles a robustly optimal rule, i.e., a monetary policy rule that implements the optimal plan and that is also completely robust to the specification of exogenous shock processes.     

Rules of the game: constructing norms of influence,subordination and constraint in IT planning

This paper examines how norms develop and influence the planning of technological and organizational change. A case study highlights the influences of a broadly held management innovation as it is introduced into an existing organizational culture, demonstrating how norms play a role in attempts to introduce technical and management innovations. In the case, three sources of normative structuring—business process re-engineering, the consultant, and the target organization's business environment—converged to create new rules defining how to conceptualize the problem space, the appropriate ways to approach problems, who had actionable authority and how ideas were to be expressed. The emergent normative context trapped the group in a malfunctioning process and eliminated opportunities to question the process or to suggest alternative directions. This case highlights how analyzing normative systems holds promise to improve scholarly understanding of organizational technologies and to refine managerial tools for technological and organizational innovation.     

Long-term interest rates,risk premia and unconventional monetary policy

We study two kinds of unconventional monetary policies: announcements about the future path of the short-term rate and long-term nominal interest rates as operating instruments of monetary policy. We do so in a model where the risk premium on long-term debt is, in part, endogenously determined. We find that both policies are consistent with unique equilibria, that, at the zero lower bound, announcements about the future path of the short-term rate can lower long-term interest rates through their impact both on expectations and on the risk premium and that long-term interest rate rules perform as well as, and at times better than, conventional Taylor rules. With simulations, we show that long-term interest rate rules generate sensible dynamics both when in operation and when expected to be applied.     

Expected Precision of Estimation and Probability of Ruling Out a Hypothesis Based on a Confidence Interval

Interval estimation is an important objective of most experimental and observational studies. Knowing at the design stage of the study how wide the confidence interval (CI) is expected to be and where its limits are expected to fall can be very informative. Asymptotic distribution of the confidence limits can also be used to answer complex questions of power analysis by computing power as probability that a CI will exclude a given parameter value. The CI‐based approach to power and methods of calculating the expected size and location of asymptotic CIs as a measure of expected precision of estimation are reviewed in the present paper. The theory is illustrated with commonly used estimators, including unadjusted risk differences, odds ratios and rate ratios, as well as more complex estimators based on multivariable linear, logistic and Cox regression models. It is noted that in applications with the non‐linear models, some care must be exercised when selecting the appropriate variance expression. In particular, the well‐known ‘short‐cut’ variance formula for the Cox model can be very inaccurate under unequal allocation of subjects to comparison groups. A more accurate expression is derived analytically and validated in simulations. Applications with ‘exact’ CIs are also considered.     

Knowledge across cultures in the construction industry: sustainability,innovation and design

In the construction industry both the design and management processes differ significantly from the stylised models usually promoted in the academic and business press. To the complexity that is normal business in construction industry projects add the uncertainty associated with the changing legal and ethical imperatives of sustainable development and the result is a mess. Innovative products, together with the companies that make them, are being built on the back of a rigged market in recycled raw materials and policy changes are spawning unintended consequences.Making sense of those processes that use knowledge about sustainability, at the level of the firm, is particularly daunting because companies behave differently in different international contexts. The problem is further complicated by the collaborative nature of projects; specialization and the need to communicate with and between experts increases both costs and uncertainties.We discuss a fundamental tension between understanding knowledge creation and use, and the drive to capture processes in formal documents and systems.We propose similarities between developments in the field of sustainability and developments in the field of risk, with risk having the advantage of being further down the evolutionary line. Both fields have strong dimensions of formal rules and socio-economic behaviours. Such complexity, we argue, requires a number of perspectives to make sense of how knowledge is used in construction and allied industries.     

Optimal monetary policy in a new Keynesian model with animal spirits and financial markets

This article presents a macro-finance-interaction model that integrates a NKM with bounded rationality and an agent-based financial market model. We derive four interactive channels between the two sectors where two channels are strictly microfounded. We analyze the impact of the different channels on economic stability and derive optimal (conventional and unconventional) monetary policy rules. We find that coefficients of optimal Taylor rules do not significantly change if financial market stabilization becomes part of the central bank׳s objective function. Additionally, we show that rule-based, backward-looking monetary policy creates huge instabilities if expectations are boundedly rational. Our model is externally validated by showing that it generates fat tailed output growth rates.