Mismatch Explanations of European Unemployment : A Critical Evaluation

Examining the sources of European unemployment, this work asks whether the mismatch hypothesis is valid. Introducing the theory of spurious mismatch trends, the author explains the basics in a straightforward manner.

1. Introduction.- 1.1. European Unemployment and the Mismatch Hypothesis.- 1.2. The Conceptual Framework followed in this Book.- 1.3. Overview and Results.- 2. Do Aggregate Measures of Mismatch Measure Mismatch? A Time Series Analysis of Existing Concepts.- 2.1. Introduction.- 2.2. Some Puzzling Evidence.- 2.3. Measuring Mismatch: Theoretical Foundations.- 2.4. Measurement Problems.- 2.5. Disaggregation and Unobserved Heterogeneity.- 2.6. Time Series Analysis.- 2.7. Testing for Unit Roots.- 2.8. On the Magnitude of Drifts in Macroeconomic Mismatch Time Series.- 2.9. Some Simulation Experiments.- 2.10. Concluding Remarks.- Appendix A2.- 3. Disaggregate Matching Functions, Spurious Mismatch and Occupational Reallocation in Germany.- 3.1. Introduction.- 3.2. Aggregate Matching Functions: Theoretical Framework.- 3.3. Aggregate Matching Functions in West Germany.- 3.4. Spurious Matching Functions.- 3.4.1. The Econometric Theory of Spurious Matching Functions.- 3.4.2. Simulated Evidence.- 3.5. Disaggregate Matching Functions using a Panel of Occupational Groups.- 3.5.1. Occupational UV-curves.- 3.5.2. Nonsense Regressions with Panel Data?.- 3.5.3. Panel Data Estimations for Disaggregate Matching Functions.- 3.5.4. Substituting the Time Trend by Economic Variables.- 3.5.5. Period Effects and the Identification of Mismatch.- 3.6. On Occupational Reallocation: Theoretical and Empirical Aspects.- 3.6.1. Matching Functions and the Adjustment of Unemployment/Vacancy Ratios.- 3.6.2. Empirical Evidence.- 3.7. Understanding the Matching of Apprentices.- 3.7.1. The Economic Problem.- 3.7.2. Towards a Reduced-Form-Matching Function for Apprentices.- 3.7.3. Panel Estimations.- 3.7.4. Backward-Looking Behaviour and Future Rigidities.- 3.8. Concluding Remarks.- Appendix A3.- A3.I. Data.- A3.II. Spurious Regressions.- A3.III. List of Occupational Groups.- A3.IV. Panel Data Modelling.- 4. Matching and New Technologies: Does Unmeasured Ability Explain the Higher Wages of New-Technology Workers?.- 4.1. Introduction.- 4.2. Matching, Mobility, and Unmeasured Ability.- 4.3. The Micro Datasets: Presentation and Descriptive Analysis.- 4.3.1. INSEE Data Sources.- 4.3.2. The Definition of "New Technology" Categories.- 4.3.3. "New Technologies" and "Organization of the Work Place".- 4.3.4. Variables Representing the Firm-Level Background of Individual Workers.- 4.4. Cross-Sectional Results.- 4.4.1. Specifying the Wage Equation.- 4.4.2. Some Theoretical and Empirical Reasons to include Firm-Level Variables.- 4.4.3. The Impact of New Technologies on Wages: Global Results.- 4.4.4. The Impact of New Technologies on Occupational Wages.- 4.4.5. Mismatch Related to New-Technology use.- 4.5. Wages and New Technologies: Evidence from Panel Data.- 4.5.1. Construction of Panel Data.- 4.5.2. The Impact of New Technologies on Wages: Fixed-Effect Modelling.- 4.6. Concluding Remarks.- Appendix A4.- A4.1. Descriptive Statistics.- A4.II. Definition of Educational Degrees.- A4.III. Additional Cross-Sectional Results.- 5. Conclusions.- 6. References.