Phillip Fanchon

Estimating VAR models under non-stationarity and cointegration: alternative approaches for forecasting cattle prices

Multivariate VAR models estimated with non-stationary data raise difficult econometric questions because differencing to achieve stationary can introduced distortions into multivariate models. Three approaches have been suggested for estimating such models:(1) Vector error correction (VEC) models difference the data to achieve stationary and use an error correction term to replace the long-run information lost through differencing; (2) VAR models can be estimated with raw data in levels if the non-stationary data is also cointegrated because recent theoretical work proves that estimation with such data will yield consistent parameter estimates; (3) Bayesian parameter estimates are not affected by non-stationarity, although some analysts argue that Bayesian analysis is not appropriate for data that is also cointegrated. A multivariate cattle price model provides a good framework for comparing these approaches because the major variables are both non-stationary and cointegrated, and because the models opti...

Variable selection for dynamic measures of efficiency in the computer industry

Data Envelopment Analysis (DEA) measures of efficiency are very sensitive to the choice of variables for two reasons: the number of efficient firms is directly related to the number (n) of variables and the selection of the n variables greatly affects the measure of efficiency. A methodology is proposed which identifies the optimal number of variables, and which identifies the contribution of each variable to the measure of efficiency. The computer industry is used as an example to illustrate the method.

Benefits and pay: The economics of military compensation∗

This paper develops a simple analytical framework which captures the economic impact of benefits on both employer and employee decision‐making. It is within this framework that the role of benefits in the military compensation equation is explored. It is demonstrated that employer and employee decisions concerning an appropriate wage‐benefit mix can have significant and predictable impacts on hiring, retention, labor costs and the characteristics of individuals that make up the armed forces.

Efficiency, market dynamics and industry growth

Technology, Efficiency and Market Structure Introduction Technology Creation and Diffusion Efficiency Models of Industry Growth Industry Growth in Cournot-Nash Framework Concluding Remarks Efficiency Models of Industry Growth Introduction Production and Cost Dynamics Adjustment Cost Dynamics Scale Economies and Learning by Doing Pareto Efficiency Frontier: DEA approach Industry Growth and Optimal Investment Concluding Remarks Growth of High-Tech industries: Computers and Pharmaceuticals Introduction Measuring Production Efficiency and Growth Stochastic Frontier Analysis DEA Models Efficiency in Computer Industry Efficiency in Pharmaceutical Industry Concluding Remarks Pricing Strategies under Innovations Introduction R&D and Market Structure Strategies of a Dominant Firm Limit Pricing with Technological Change and Internal Finance Appendix Dynamic Models of Productivity and Efficiency Introduction Dynamic DEA Models Growth and Technology Industry Evolution and Innovation Hypercompetitive Market Structures Efficiency and Growth of the Telecom Industry Introduction Entry and Efficiency Market Deregulation Capital Expenditures Geographic Separation of Markets R&D and Productivity Measuring Efficiency Ingredients for Efficiency Concluding Remarks

A model of periodic job training

This paper examines conditions under which a demand-constrained, cost-minimizing firm will provide industry-specific on-the-job-training to its employees, when a flexible stock of outside labor is available for hire. The term industry-specific is used to describe training with general components valued by other firms in the industry. This definition of on-the-job-training offers the possibility that trained workers could be poached by competing firms and provides limited opportunities for newly trained workers to seek alternative employment. The firms decisions involve whether or not to invest in on-the-job-training, and whether to use in-house labor exclusively or a mix of in-house and outside labor. The cost-minimizing strategy is crucially dependent upon the mutual loyalty of the firm and its workers.

Design of Optimal Policies: A Variable Structure Control Approach

This paper introduces methods of variable structure control (VSC) theory to economists. The VSC design is based on closed loop optimal control solutions. It is shown that VSC can yield stable solutions in the presence of parameter errors whereas conventional closed loop optimal control solutions become unstable. The methodology is applied to a simple economic model.

Efficiency and Growth of the Telecom Industry

The telecommunications industry has evolved rapidly in the last two decades, when the maturing wireless technology sharply eroded the dominance of fixed-lines providers. The decline in market share of fixed lines has been especially strong in countries where the traditional cable infrastructure was not well developed. Three interacting forces drive the transformation of the industry: (1) Market structure and deregulation, (2) innovation, and (3) capital expenditures by the firms. Stimulating competition can increase market efficiency as a more competitive market stimulates the degree of innovation undertaken both by incumbents and by entrant operators. Vast arrays of telecommunications policies throughout the world affect the dynamics of entry through the control of network availability and connection charges. Regulating agencies can affect market prices, and consequently influence both profits and the incentive to invest in R&D and equipment. The sharp interest in the interaction between these forces has generated a voluminous literature. In particular, Laffont and Tirole (2000) provide a comprehensive overview of the main issues in the economics of the telecommunications sector.

Technology, Efficiency and Market Structure

Technology affects economic growth and development in many ways. It comes in many forms and affects firm growth and industry evolution. Three specific economic meanings of technology and technological progress have been emphasized in dynamic economics. First, it measures the dynamic shift over time of the production frontier, i.e., the way the various inputs are utilized to produce outputs over time. Technological progress may be partly embodied in the individual inputs like labor and capital, or it may reflect the joint productivity effects of some or all inputs. Second, technology may take the form of new research ideas and knowledge as human capital.

Pricing Strategies Under Innovation

Many key scientific discoveries are accidental, and applications of scientific research are often in areas far removed from the origin of the discovery, which explains why it is so difficult to model, or even measure, the various benefits of investment in R&D. The task is complicated further if one tries to model the likely spillover and other unintended effects. Firm-level data from innovation surveys1 has revealed that there is a great heterogeneity of innovation patterns across firms, sectors and locations, and that the time required to reap the full benefits of R&D may be quite long. Innovations can take many forms. In the Schumpeterian framework all innovations are dynamic and they alter the static competitive equilibrium to a significant degree. Changing technology, introducing new product lines and expanding markets through scale economies highlight some of the features of innovations. If successful, R&D expenditures generate technological advances that ultimately provide a firm with a competitive advantage.2 Even if not successful, R&D still provide some experience to the firm and enhances its ability to improve its production, its management, and its ability to exploit knowledge, including the exploitation of R&D advances by other firms.

Dynamic Models of Productivity and Efficiency

In recent times competition has been most intense in the modern high-tech industries such as microelectronics, semiconductors and personal computers. Product and process innovations, economies of scale and learning by doing have intensified the competitive pressure leading to the decline in unit production costs and prices. Thus the average industry productivity growth (i.e. total factor productivity growth in a specific high-tech industry) has achieved a rate of 2.0% growth per year over the period 1958–96 for the US electronic equipment, which includes semiconductors and communications equipment. High productivity growth led to falling unit costs and prices. Our object here is to formulate a set of nonparametric and semi-parametric models of dynamic production and cost frontiers.