Climate, jobs, and inequity : models of worker mobility and distribution under carbon pricing

Employment impacts are front of mind in debates on carbon pricing among policy makers and in the popular press. Key in this debate is extent to which workers in contracting emissions-intensive industries will be able to find work elsewhere, and the magnitude of their earnings losses. Moreover, to the extent that workers in emissions-intensive industries are disproportionately lower-income—or if such industries are unique in being sources of high-paying jobs for those with comparatively less education—, this could also be an equity issue. Yet, the CGE models underlying policy decisions are usually ill-suited for examining employment impacts in the disaggregated manner that the above concerns would demand. I therefore present an empirically grounded method to introduce imperfect labor mobility into a computable general equilibrium (CGE) framework in Chapter 2, using sector-specific human capital and non-pecuniary preferences. Specifically, a one-period CGE model is linked and iteratively solved with an econometrically estimated labor model of sectoral choice involving worker characteristics and predicted wages based on sector-specific skills accumulated through experience. This setup allows me to introduce imperfect labor mobility in two ways. First, workers have sector-specific experience, which enter the wage equation and introduce lost wages upon moving across sectors. Second, individuals' choices over the work alternatives are based on a random utility framework in which workers' preferences are affected by demographic and household characteristics, in addition to the wages obtained in that sector. I apply this linked CGE--microsimulation model of imperfect labor mobility to an analysis of the impact of a carbon tax on the U.S. economy in Chapter 3. I find that a carbon tax set at a central estimate of the social cost of carbon leads to a modest change in aggregate employment, ranging from a 0.06% reduction to a 0.04% gain (71,000 jobs lost to 42,000 jobs gained), depending on revenue recycling assumptions, though the impact is much larger in the fossil fuel extraction sector, where both wages and employment fall. Though imperfect labor mobility is welfare-reducing, the revenue recycling assumptions drive the distributional outcomes. In particular, rebating the carbon tax revenue on a per-capita basis is highly progressive, as found in the literature. On the other hand, using the revenue to fund a carbon tax cut is the most efficient and leads to a slight increase in employment relative to the no-policy case. The microsimulation structure of the model allows me to evaluate a set of illustrative retraining programs. I find that though such programs increase the welfare of retrained workers, the low responsiveness of sectoral choice to wages means that gains are small and largely from modest increases in coal wages, rather than a movement into the target sectors. This said, fossil-fuel workers represent such a small share of the overall workforce that such a program can be funded while still leaving the vast majority of revenue for other uses. One hypothesis for the relative ineffectiveness of a retraining program is that workers tend not to move across geographies and that jobs in the target sector may not exist in the locality in which the worker was laid off—a dimension that I do not consider in the above CGE--microsimulation model. I explore this hypothesis in Chapter 4, estimating the effect of the share of the local workforce that a worker's pre-layoff industry represents on various labor market outcomes. I find average monthly earnings decrease with this share, with a one-standard-deviation increase leading to a $4,564 greater earnings loss over the course of the first 24 months following layoff. This effect appears to be driven primarily by a lower share of such workers switching industries and a lower reemployment rate for workers laid off from industries comprising a large share of the local workforce. This highlights the need to consider local labor market conditions when designing retraining and other adjustment assistance policies. The extent to which intersectoral labor mobility frictions are driven by the geographic distribution of industries will impact the appropriate policy response

Advisor: Kolstad Charles D. 
Weyant John P. (John Peter)
Goulder Lawrence H. (Lawrence Herbert)
Wara Michael