Abstract
Abstract Employment in the US logging industry has been declining over the past few decades and fell to a 20-year low following the 2008 economic recession. This study investigates the drivers of employment in the US logging industry from 2007 to 2017, using a directed acyclic graph (DAG). This approach is applied for the first time to disclose the contemporaneous causal relations among employment, wages, mechanization, production level, and product prices in the logging industry. Forecast error variance decomposition (VD) is further used to examine the long-run dynamic relationships between these variables. The results show that the product price directly affects employment and indirectly promotes employment through wages. The results of VD show that mechanization has an increasing long-term effect on employment.
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