A theoretical and empirical analysis of an adverse selection model of wages and strikes
Bibliographic record
Abstract
Traditional views are that strikes are the result of mistakes in bargaining [Reder and Neumann (1980), Kennan (1980)] or that they are due to irrational or politically motivated behaviour [Ashenfelter and Johnson (1969)]. However, according to recently developed models of strikes based on the theory of asymmetric information, strikes are not merely mistakes, nor are strikes the outcome of irrational behaviour. The two-type adverse-selection models of Morton (1983) and Hayes (1984) and the sequential bargaining models of Fudenberg, Levine and Ruud (1984) and Tracy (1987) assume that the firm is better-informed than the union about the firm's level of profitability. Since a more profitable firm can afford to pay higher wages, it may be in the interest of the union to elicit information about the level of profitability from the firm. In the asymmetric information models, the union uses strikes to elicit the information from the firm. One of the contributions of the present dissertation is to propose a variant of Hayes' adverse-selection model which may be generalized to an arbitrary number of firm types. Two key results are derived. First, wages and strikes are predicted to satisfy what is called a monotonicity property. Second, there are two kinds of equilibria in the model: a separating equilibrium, which includes the possibility that a strike is the outcome of negotiations, and a pooling equilibrium, which rules out the possibility of a strike. In addition, comparative statics results are derived for all the exogenous variables in the theoretical model, significantly extending the results of Hayes (1984). Without exception, exisiting empirical work examining the asymmetric information theory of strikes estimates separate reduced form equations for strike incidence, strike duration and, to a lesser degree, wage levels. According to the asymmetric information theory, however, wage levels and strike lengths are jointly endogenously determined given values for exogenous variables. A major contribution of the present dissertation is the derivation of a maximum likelihood procedure which allows for joint estimation of strike duration and wage level equations. This econometric model has several attractive features. First, the estimating equations are interpreted as linear approximations to the structural equations of the theoretical model. Second, the likelihood function is derived using the monotonicity property of wages and strikes predicted by the theoretical model. Third, the model allows the data to estimate which observations correspond to separating equilibria and which to pooling equilibria. Fourth, the estimates may be used to calculate the probability of a separating equilibrium at each observation. Finally, it is argued that since the endogenous variables in many models of adverse-selection exhibit a monotonicity property, the econometric model proposed here potentially has a much wider application than simply as a model of wages and strikes. Another contribution of the present dissertation is the assembly of a data set which merges information from 2,459 contracts in Canadian industries covering the period 1964-86 with data specific to the firm. Explanatory variables implied by the theoretical model are then used to test the comparative statics predictions in the econometric model of wages and strikes. The empirical results confirm all but one of the comparative statics predictions of the theory, and the econometric model fits the data well. Pooling equilibria are estimated to be present in approximately 13% of the contracts. In addition, the results are entirely consistent with the stylized facts concerning the behaviour of strikes over time, the business cycle and relative to other variables.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.028 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".