A regional unemployment model simultaneously accounting for serial dynamics, weak and strong cross-sectional dependence

Paul Elhorst (University of Groningen)

Riccardo Faini CEIS Seminars

Riccardo Faini CEIS Seminars
When

Friday, April 15, 2016 h. 12:00-13:30

Where
Room B - 1st floor
Description

 joint with Solmaria Halleck Vega (University of Groningen)

Regional unemployment rates tend to be strongly correlated over time, parallel the national unemployment rate, and be correlated across space. We address these key stylized facts by linking different strands of literature into a unified methodology to investigate regional unemployment disparities. This methodology simultaneously accounts for serial dynamics and so-called strong and weak cross-sectional dependence. It generalizes previous approaches focusing on serial dynamics in combination with weak or strong cross-sectional dependence only, as well as recent approaches employing two-step procedures to account for both types of cross-sectional dependence. We apply these methods using provincial level data for the Netherlands. The substantial and persistent division between high and low unemployment clusters makes it an interesting case, and data availability since the early 1970s enables a comparison between prior periods of downturn and recovery to the recent economic crisis. It is shown that our simultaneous model is more general and that the empirical results produced by previous approaches may lead to biased inference.

Key words: Regional unemployment, strong and weak cross-sectional dependence, dynamic spatial panel models, the Netherlands

JEL classification: C23, C33, C38, R23

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