A Quest for Leading Indicators of the Turkish Unemployment Rate
This paper examines various variables that are likely to be associated with the Turkish non-agricultural unemployment rate in search of indicators to summarize and forecast the state of the labor market. We consider a total of 72 series that reflect aggregate economic activity, labor market conditions, expectations over future economic activity, global economic trends and credit conditions. We use Granger causality tests, correlation analyses and individual out of sample forecast performance of these series to assess their informativeness about the unemployment rate. We find that Business Tendency Survey indicators and some series that measure the global economic conditions satisfy all three criteria of informativeness. Moreover, the composite index constructed from series selected based upon out of sample predictive power improves short-term forecast performance of the autoregressive benchmark model, where we use only lagged values of the unemployment rate.
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