Climate variability reduces employment in New England fisheries

Abstract

Climate change is already affecting fish productivity and distributions worldwide, yet its impact on fishing labor has not been examined. Here I directly link large-scale climate variability with fishery employment by studying the effects of sea-surface pressure changes in the North Atlantic region, whose waters are among the world’s fastest warming. I find that climate shocks reduce not only regional catch and revenue in the New England fishing sector, but also ultimately county-level wages and employment among commercial harvesters. Each SD increase from the climatic mean decreases county-level fishing employment by 13%, on average. The South Atlantic region serves as a control due to its different ecological response to climate. Overall, I estimate that climate variability from 1996 to 2017 is responsible for a 16% (95% CI: 10% to 22%) decline in county-level fishing employment in New England, beyond the changes in employment attributable to management or other factors. This quantitative evidence linking climate variability and fishing labor has important implications for management in New England, which employs 20% of US commercial harvesters. Because the results are mediated by the local biology and institutions, they cannot be directly extrapolated to other regions. But they show that climate can impact fishing outcomes in ways unaccounted by management and offer a template for study of this relationship in fisheries around the world.

Nominal Wage Rigidity in Village Labor Markets

“…In addition, as in the model, I assume the shocks are transitory: rainfall in a given year affects TFP in only that year. 24 In the absence of rigidities, the following simple model captures the effects of transitory shocks on equilibrium wages: (7) ln…”

“…In contrast, under Null Hypothesis (iii), ψ 2 = ψ 3 = ψ 4 = 0 . This again means that under the null, specification (9) should reduce to specification (7).…”

“…If a district experiences a transitory positive shock (and therefore has a ratcheted wage in the following year), total agricultural employment is 9 percent lower in the following year than if the lagged positive shock had not occurred. 7 In contrast, these shocks have no effect on non-agricultural hiring. Overall, these employment dynamics are consistent with boom and bust cycles in village economies.…”

“…Below, I use the results to directly document a lack of serial correlation in shocks, and to rule out persistent productivity impacts of shocks.25 Note that this equilibrium wage model can also be expressed in a first differences framework. It is straightforward to verify that writing equation(7)for ln w d,t−1 and subtracting from(7) gives: ln w dt − ln w d,t−1 = α 1 (Po s dt − Po s d,t−1 ) + α 2 (Ne g dt − Ne g d,t−1 ) + I t + ξ dt , where I t ≡ ln p t − ln p t−1 is the inflation level. The α 1 and α 2 coefficients have the same expected value in both specifications.…”

Skilful prediction of cod stocks in the North and Barents Sea a decade in advance

“…Climate variability has been a subject of interest for ecologists primarily because variations in climate often have a strong impact on ecological systems 1 . Marine resources, such as fish stocks, have been shown to be strongly influenced by climate variability [2][3][4] , with changes in productivity resulting in huge consequences for socio-economic systems relying on such resources 5,6 . In the Anthropocene, with the threat of climate change, understanding the impact of climate variability on marine ecosystems and resources has become even more central, since climate variability at interannual to decadal timescales can exacerbate the magnitude of ongoing long-term climate change 7,8 .…”