The employment - wage pattern conundrum: institutions, policies and labour market outcomes

Labour market reforms encompass a wide set of measures, which may have varying and non-linear effects on wage growth. Established datasets to evaluate reform effects such as the EU LABREF dataset, the OECD SPIDER
database or the ILO Inventory of Labour Market Policy Measures only include very broad categories of labour market reforms. The Eurostat labour market policy statistics and the OECD employment database provide high-level
data on labour market institutions including EPL, UB replacement rates, ALMP spending and the number of enrolled participants. However, these datasets do not contain sufficient differentiation between different types
of reforms and measures of benefit conditionality.
I intend to take a more comprehensive approach and plan to assemble country-level data of implemented labour market reforms and ALMP policies over the last two decades in a set of European economies. The ICTWSS dataset
(Visser 2015) comprises a comprehensive collection of codified data on labour market institutions, mainly limited to wage setting institutions and social partners, which is relevant to use for CB data. The MISSOC dataset contains
a relevant summary on unemployment benefits and the Comparative Unemployment Benefit Conditions & Sanctions dataset (Knotz & Nelson 2018) documents the increase in the strictness of unemployment benefit
conditions and sanctions over the past decades. Text mining and data scrapping tools will help to collect and codify textual data from MISSOC and national sources (e.g. by using the R package tm). After the data collection, I plan
to follow three parallel approaches to answer the research question and its sub-questions. The first approach is intended to focus on all European Union countries, while the second and third approaches are planned to focus
on a subset of European Union countries for which adequate data are available.
1. On a country level, I plan to observe how major labour market flexibilizing reforms play out on aggregate wage growth. Using time-varying variables such as EPL strength, UB replacement rate, CB coverage rate
and ALMP spending will allow applying a regression discontinuity design to the point in time when a major labour market reform was implemented. This will allow to observe any break in the effect of the variables
on aggregate wage growth and its distribution before and after labour market reforms, and to detect heterogeneity between countries and different types of reforms
2. Complementarily, I am envisaging to take a more granular approach for selected countries. I will estimate the effects of labour market flexibilizing reforms on wage growth of different income deciles using micro
panel data for available countries (e.g. SOEP for Germany, BHPS/ASHE for the UK) and repeated cross-sectional micro data for others (e.g. EU-SILC weighted by EU LFS). The research strategy will follow a
difference-in-difference design to observe the Phillips curve link and distributional differences across regions, sectors, occupations and income deciles.
3. In the third approach, I plan to study the interactions of different policy changes over time. Established research methods often struggle to study different combinations of reforms and their time sequencing.
Applying supervised machine learning (e.g. using the R package caret) allows studying nested data, which is particularly important as we can expect the effects of labour market policy changes to be path dependent
on previous reforms and to have non-linear effects on wage growth and its distribution.