Bargaining Power and Wage-Employment Contracts in a Unionized Industry

Abstract

Input and output data are used in conjunction with negotiated wages and employment to estimate a fully specified bargaining model between a labour union (the International Woodworkers of America) and representatives from the British Columbia Wood products industry. Bargaining powers are modelled as functions of exogenous variables believed to have influenced the parties' relative strike costs. The estimated bargaining powers are plotted over time and compared to the proportion of rents captured by each party. Parameters of the union utility function and the firms' technology are also estimated and hypothesis tests are conducted on various aspects of the model. There are still relatively few studies in which fully specified models of bargaining between labour unions and firms are estimated. This reflects both the extensive data requirements and the complexity of the models involved. A fully specified model includes a representation of the firms' objectives and technological constraints, the union's goals and constraints and the bargaining structure. Furthermore, even when micro data are available, usually more than two parties are involved i.e. firms will negotiate with several unions and each union will have to deal separately with the many firms operating within the industry. This complicates the modelling of the bargaining setting considerably. In this study, data on the wood products industry in British Columbia, Canada are analyzed. During the period under study (1963-1983), negotiations in this industry were highly centralized. In fact, the bargaining setting can be described as a bilateral monopoly between the International Woodworkers of America (IWA), a powerful and stable union and the Forest Industrial Relations, an employer association representing firms in the industry. This data set includes information on outputs and nonlabour inputs thus allowing the calculation of profits and the joint determination of output and other inputs along with employment and wages. A structural model with four dependent variables-wages, employment, output and a materials and supplies input-is estimated. Firms are assumed to maximize profits and union objectives are modelled by a CES utility function with employment and the difference between union wages and alternative wages as arguments. Given a representation for the firms' technology and the union preferences, a