Distributed lags and intermediate good imports

In this paper we draw upon some recent developments in the theory of dynamic economics and econometrics to characterize the time series behavior of intermediate good imports. It is shown that adjustment costs, delivery lags, and inventory holding costs considerations lead to distributed lag import demand functions that are not subject to the Nerlove (1972) and Lucas (1976) critiques of ad hoc and fixed distributed lag modelling.     

Multivariate regression models for panel data

The paper examines the relationship between heterogeneity bias and strict exogeneity in a distributed lag regression of y on x. The relationship is very strong when x is continuous, weaker when x is discrete, and non-existent as the order of the distributed lag becomes infinite. The individual specific random variables introduce nonlinearity and heteroskedasticity; so the paper provides an appropriate framework for the estimation of multivariate linear predictors. Restrictions are imposed using a minimum distance estimator. It is generally more efficient than the conventional estimators such as quasi-maximum likelihood. There are computationally simple generalizations of two- and three-stage least squares that achieve this efficiency gain. Some of these ideas are illustrated using the sample of Young Men in the National Longitudinal Survey. The paper reports regressions on the leads and lags of variables measuring union coverage, SMSA, and region. The results indicate that the leads and lags could have been generated just by a random intercept. This gives some support for analysis of covariance type estimates; these estimates indicate a substantial heterogeneity bias in the union, SMSA, and region coefficients.     

Export restraints in a model of trade with capital accumulation

This paper examines the impact of voluntary export restraints (VERs) in an international duopoly modeled as a differential game. With a Ramsey capital accumulation dynamics, the game admits multiple steady states, and a VER cannot be ‘voluntarily’ employed by the foreign firm in case of Cournot behavior in demand substitutes. Hence, the dynamic framework confirms the results of the VERs literature with static interaction in output levels. In the case of price behavior, the adoption of an export restraint may increase the profits of both firms if products are substitutes and the steady state is ‘market-driven’. However, contrary to the acquired wisdom based upon the static approach, the dynamic analysis also admits an equilibrium outcome, identified by the Ramsey golden rule, where the incentive to adopt a VER is ruled out, irrespective of whether firms are quantity- or price-setters.     

Bayesian estimation and model selection for spatial Durbin error model with finite distributed lags

In this paper we investigate a spatial Durbin error model with finite distributed lags and consider the Bayesian MCMC estimation of the model with a smoothness prior. We study also the corresponding Bayesian model selection procedure for the spatial Durbin error model, the spatial autoregressive model and the matrix exponential spatial specification model. We derive expressions of the marginal likelihood of the three models, which greatly simplify the model selection procedure. Simulation results suggest that the Bayesian estimates of high order spatial distributed lag coefficients are more precise than the maximum likelihood estimates. When the data is generated with a general declining pattern or a unimodal pattern for lag coefficients, the spatial Durbin error model can better capture the pattern than the SAR and the MESS models in most cases. We apply the procedure to study the effect of right to work (RTW) laws on manufacturing employment.     

Granger causality in risk and detection of extreme risk spillover between financial markets

Controlling and monitoring extreme downside market risk are important for financial risk management and portfolio/investment diversification. In this paper, we introduce a new concept of Granger causality in risk and propose a class of kernel-based tests to detect extreme downside risk spillover between financial markets, where risk is measured by the left tail of the distribution or equivalently by the Value at Risk (VaR). The proposed tests have a convenient asymptotic standard normal distribution under the null hypothesis of no Granger causality in risk. They check a large number of lags and thus can detect risk spillover that occurs with a time lag or that has weak spillover at each lag but carries over a very long distributional lag. Usually, tests using a large number of lags may have low power against alternatives of practical importance, due to the loss of a large number of degrees of freedom. Such power loss is fortunately alleviated for our tests because our kernel approach naturally discounts higher order lags, which is consistent with the stylized fact that today’s financial markets are often more influenced by the recent events than the remote past events. A simulation study shows that the proposed tests have reasonable size and power against a variety of empirically plausible alternatives in finite samples, including the spillover from the dynamics in mean, variance, skewness and kurtosis respectively. In particular, nonuniform weighting delivers better power than uniform weighting and a Granger-type regression procedure. The proposed tests are useful in investigating large comovements between financial markets such as financial contagions. An application to the Eurodollar and Japanese Yen highlights the merits of our approach.     

Modeling monetary policy as an unobserved variable

This paper presents a model of the U.S. Monetary Authority. It is assumed that monetary policy is a single dimensioned unobserved variable that links changes in a set of ‘causal’ variables representing economic goals and changes in money market ‘indicator’ variables. Several issues are examined pertaining to the weights attached to the causal variables including: the lag structure, changes over time, and asymmetric effects of positive and negative changes. As a by product of the model, the paper presents an estimated index of monetary policy for the years 1955–1975.     

Unpacking the client(s): Constructions, positions and client–consultant dynamics

Research on management consultancy usually emphasizes the role and perspective of the consultants. Whilst important, consultants are only one element in a dynamic relationship involving both consultants and their clients. In much of the literature, the client is neglected, or is assumed to represent a distinct, immutable entity. In this paper, we argue that the client organisation is not uniform but is instead (like organisations generally) a more or less heterogeneous assemblage of actors, interests and inclinations involved in multiple and varied ways in consultancy projects. This paper draws upon three empirical cases and emphasizes three key aspects of clients in the context of consultancy projects: (a) client diversity, including, but not limited to diversity arising solely from (pre-)structured contact relations and interests; (b) processes of constructing ‘the client’ (including negotiation, conflict, and reconstruction) and the client identities which are thereby produced; and (c) the dynamics of client–consultant relations and how these influence the construction of multiple and perhaps contested client positions and identities.     

Externalities and Industrial Development

Using panel data for five capital goods industries, this paper estimates dynamic externalities. In contrast to previous studies, panel data allow separation of externalities from fixed effects and identification of a lag structure. I find strong evidence of Marshall–Arrow–Romer (MAR) (own industry, or localization) externalities. For Jacobs (urbanization) externalities effects are smaller. In terms of lag structure, for MAR externalities the biggest effects are typically from several years ago, but die out after six years. For urbanization phenomena, effects persist to the end of the time horizon of the data–eight or nine years back.     

Measuring the impact of R&;D on Productivity from a Econometric Time Series Perspective

In this paper we argue that the standard sequential reduction approach to modelling dynamic relationships may be sub-optimal when long lag lengths are required and especially when the intermediate lags may be less important. A flexible model search approach is adopted using the insights of Bayesian Model probabilities, and new information criteria based on forecasting performance. This approach is facilitated by exploiting Genetic Algorithms. Using data on U.K. and U.S. agriculture the bivariate time series relationship between R&D expenditure and productivity is analysed. Long lags are found in the relationship between R&D expenditures and productivity in the U.K. and in the U.S. which remain undiscovered when using the orthodox approach. This finding is of particular importance in the debate on the optimal level of public R&D funding.JEL Classification: C22, C51, Q16     

中国高技术产业技术创新三阶段特征及其演变

基于投入产出分析的逻辑思路建立技术创新三阶段模型,运用链式网络DEA方法测量我国高技术产业技术创新三阶段效率,通过技术创新效率的动态变化观察高技术产业技术创新演变规律。研究发现,1996~2011年我国高技术产业技术开发阶段经历了整体上类似“U”形的变化,源于技术开发阶段的投入增多、企业重视力度加大;技术转化阶段滞后于技术开发阶段近两年的变化时期,主要起因于纯技术无效率、技术开发阶段和产业化阶段的脱节;产业化阶段滞后于技术开发阶段近5年的变化时期和技术转化阶段近3年的变化时期,主要由于产业化阶段作为技术开发和技术转化的下游阶段,偏低的技术转化率必然导致最终的产业化率极低,但改进的空间很大。     

An international study of causality-in-variance: Interest rate and financial sector returns

We demonstrate that causality-in-variance test could be employed to model the direction and lags in information flow between two variables and to avoid misspecifications. We apply this methodology to test the causality between the financial sector returns and interest rates of the G7 countries and show that the direction and the lead/lag structure of causality in the mean and the variance are more complex and dynamic than that have previously been reported. In most cases, we found two-way information flow both at the mean and the volatility level. Causality results give us insights into (i) how and when information is impacted on different market segments, and (ii) design more objective bi-variate models with the appropriate lag structure.     

Self-organized criticality in evolutionary systems with local interaction

This paper studies a stylized model of local interaction where agents choose from an ever increasing set of vertically ranked actions, e.g. technologies. The driving forces of the model are infrequent upward shifts (‘updates’), followed by a rapid process of local imitation (‘diffusion’). Our main focus is on the regularities displayed by the long-run distribution of diffusion waves and their implication on the performance of the system. By integrating analytical techniques and numerical simulations, we come to the following two main conclusions. (1) If non-coordination costs are sufficiently high, the system behaves critically, in the sense customarily used in physics. (2) The performance of the system is optimal at the frontier of the critical region. Heuristically, this may be interpreted as an indication that (performance-sensitive) evolutionary forces induce the system to be placed ‘at the edge of order and chaos’.     

Using dynamic programming with adaptive grid scheme for optimal control problems in economics

The study of the solutions of dynamic models with optimizing agents has often been limited by a lack of available analytical techniques to explicitly find the global solution paths. On the other hand, the application of numerical techniques such as dynamic programming to find the solution in interesting regions of the state was restricted by the use of fixed grid size techniques. Following Grüne (Numer. Math. 75 (3) (1997) 319; University of Bayreuth, submitted, 2003), in this paper an adaptive grid scheme is used for finding the global solutions of discrete time Hamilton–Jacobi–Bellman equations. Local error estimates are established and an adapting iteration for the discretization of the state space is developed. The advantage of the use of adaptive grid scheme is demonstrated by computing the solutions of one- and two-dimensional economic models which exhibit steep curvature, complicated dynamics due to multiple equilibria, thresholds (Skiba sets) separating domains of attraction and periodic solutions. We consider deterministic and stochastic model variants. The studied examples are from economic growth, investment theory, environmental and resource economics.     

Measurement of Dynamic Efficiency in Production: An Application of Data Envelopment Analysis to Japanese Electric Utilities

The purpose of this paper is to measure productive efficiencies when a firm employs quasi-fixed inputs that cannot be instantaneously adjusted to their optimal levels. To this end, data envelopment analysis (DEA) is extended to a dynamic framework so that investment behavior can be modelled with the efficient production frontier. Based on the work of Nemoto and Goto (1999), we show how the efficiencies of quasi-fixed inputs and their adjustment processes are evaluated. An application to Japanese electric utilities over the 1981–1995 period delivers empirically plausible results and proves the usefulness of the procedure.     

Evaluating Californian under‐age drunk driving laws: endogenous policy lags

When evaluating the effectiveness of a policy, most studies assume that the policy effect begins with the date of enactment. However, there often exists an endogenous policy lag, due to information acquisition and the cost of adjustment. Meanwhile, the policy impact may be a gradual implementation from one level to another, instead of a one‐time shift behavior. To account for these issues when evaluating the Californian under‐age drunk driving laws, this paper adopts two econometric techniques: the multiple structural change methodology and the smooth transition method. The methods detect two effective policy changes and also reveal the existence of policy lags. In addition, ignoring these lags leads to severely biased estimates of policy effects. A long transition period is identified for the first under‐age drunk driving policy, while an abrupt transition is found for the other. In summary, the paper shows that the two econometric techniques complement each other and will be useful for policy evaluation. Copyright © 2011 John Wiley & Sons, Ltd.     

Increasing e-ordering adoption: A case study

e-ordering systems are currently widely adopted by organisations. Attractive business cases, however, tend to deteriorate when intra-organisational adoption lags behind as compliance of the intended individual behaviour is not achieved in a timely fashion. This paper shows the findings of an in-depth case study aimed at identifying the effectiveness of interventions in speeding up and/or raising compliance to the intended behaviour. In the case study, the effect of mandating system usage is shown to overcome the ‘benefit imbalance’ between individuals and organisational benefits. While enforcement resulted in an initial system usage, achieving intended behaviour required additional interventions. The paper closes with theoretical and practical implications.     

Control of economic systems under the process of data improvement

The paper deals with optimal control of the systems with a certain part of economic parameters not defined completely, namely, in terms of an interval of uncertainty b ± δ. The important idea of our approach is that optimal control should take into account data improvement. The approach implies the process of introducing new data which make cost estimates more precise. The process is described as a random and exogenous one and by its nature may be named a process with ‘independent decrements’ (of entropy). The stationary model of a dynamic system is developed; the system has the interval of uncertainty as its phase point.     

Inside the queue:: hypercongestion and road pricing in a continuous time–continuous place model of traffic congestion

This paper develops a continuous-time–continuous-place dynamic economic model of traffic congestion, based on car-following theory. The model integrates two archetype congestion technologies used in the economics literature: ‘static flow congestion’ and ‘dynamic bottleneck congestion.’ With endogenous departure times and a bottleneck along the route, ‘hypercongestion’ arises as a dynamic equilibrium phenomenon on the upstream road segment. Congestion tolls based on an intuitive dynamic and space-varying generalization of the standard Pigouvian tax rule can hardly be improved upon. A naïve application of a toll schedule based on Vickrey's bottleneck model performs much worse and reduces welfare in the numerical model.     

Thy neighbor’s jobs: geography and labor market dynamics

This paper develops three explanations for the extent of correlation between neighboring geographic areas’ economic outcomes. Export-oriented firms in neighboring counties might independently produce similar goods, or might be linked directly through the production of intermediate inputs. In either case, counties are exposed to similar demand shocks. Finally, regions share markets for goods and services that are both produced and consumed locally. Empirical results suggest that much of the ‘risk’ associated with economic decline in neighboring regions can be attributed to industrial similarity rather than direct dependence of jobs in one area on jobs in another.     

Investment with an arithmetic process and lags

This paper presents an explicit solution of a simple investment problem with entry lags and when the underlying stochastic process is arithmetic. It is shown that, without abandonment, the optimal investment plan is independent of the length of the lag. Copyright © 2000 John Wiley & Sons, Ltd.