6533b86efe1ef96bd12cc19d
RESEARCH PRODUCT
Employment effects of reducing labour costs : considering potential bias in macro-estimates of the elasticity of labour demand
Jussi Huuskonensubject
meta-analysisjoustavuusMonte Carlo -menetelmätcomposition biaskysyntämeta-analyysilabour demandelasticitytyövoimameasurement errordescription
In 2016 the Finnish government decided to implement the competitiveness pact in order to increase employment. The objective is to improve cost-competitiveness by lowering labor costs in the private sector. The elasticity of labour demand plays a key role in assessing the employment effects of the competitiveness pact. The idea of this study is based on the Economic Policy Council Report (2016) which argued that the government’s elasticity estimate is very high and predicts overly optimistic employment effects. The majority of studies estimate demand elasticities using aggregate data, which is likely to produce biased estimates. The problems relate in particular to the lack of exogenous variation in labour costs, the simultaneity of demand and supply, and the possibility of composition bias. This study considers potential bias in macro-estimates of the elasticity of labour demand. In the empirical part labour demand elasticities are estimated using industry-level data that cover the years 1996-2013. The key idea is to use different wage variables. Furthermore, the effects of measurement error in working hours are examined by using Monte Carlo simulation method. The calculations show that aggregate data has a tendency to produce biased and excessively large elasticity estimates. A relevant elasticity estimate should be based on research containing plausible exogenous variation in wages. Therefore, this study contains a small meta-analysis of micro-studies examining situations where labor costs have been altered exogenously. Such studies provide elasticity estimates that can be interpreted as causal effects of reducing labour costs. These micro-studies appear to produce significantly lower elasticity estimates than macro-studies based on aggregate data.
year | journal | country | edition | language |
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2017-01-01 |