Читать книгу Extreme Events and Climate Change - Группа авторов - Страница 31

We propose a production function framework to analyze the impact of heat waves on specific crops in California. Specifically, we are proposing the framework to determine the impact of heat stress on agricultural labor and the resulting impact on crop production. The analysis of the impact of excess temperature on plant productivity has been extensive (Lobell et al., 2011; Schlenker & Roberts, 2009), but the impact of heat on the productivity of the agricultural outdoor labor less so. In essence, the analysis here complements prior work on the impact of high temperatures on crops themselves. The crops in the area under analysis are heavily irrigated, so that the impact of high temperature on crops themselves is less severe than in other geographical areas where irrigation is not the norm. Our starting point is the conceptual framework implemented by other researchers who have used output production functions to analyze the impact of heat on industrial/indoor labor (Somanathan et al., 2018), adjusted to the reality of the California agricultural sector. For example, the seasonality of harvesting activities contrasts sharply with the ability of non‐agricultural workers to work indoors most of the year, especially with air conditioning. In addition, we take into consideration the role of product differentiation with respect to crop prices and requirements for land and labor. Finally, we include specific seasonality of agricultural production for different crops, particularly with respect to harvesting periods.

A generalized production function shows the relationship between output quantity Y and the required inputs and their quantities such as labor L, capital K, and fertilizer X for example:

(1)

Eq. (1) can take many functional forms. As we indicated previously, the relationship between outdoor temperature and outdoor labor productivity is likely to be nonlinear. A Cobb‐Douglas specification for Eq. (1) would therefore seem reasonable:

(2)

where:

 Y= Crop production level

 L(T)= Function indicating the relationship between labor and temperature in the production of Y

 T= Observable outdoor temperature

 E= Area harvested in the production of crop Y

 A= capital requirement to produce crop Y

Because the relationship between the HI and a worker’s ability to complete a task is assumed to be nonlinear, one can hypothesize the existence of a threshold heat index value, HI_c, after which labor productivity declines (Somanathan et al., 2018). If workers are able to perfectly adapt to the outdoor temperature via proper clothing, regular breaks, water availability at all times, and regular water intake, then workers would be unlikely to be affected by high temperatures, in essence, negating the existence of HI_c or making HI_c of such value that it does not affect their work. HI_c is then a value we need to estimate empirically. Our ongoing fieldwork experience and published research indicates that this is not the case and that in fact there is such a value, HI_c, after which productivity declines (Crowe et al., 2013; Kjellstrom et al., 2016; Stoecklin‐Marois et al., 2013).

We hypothesize that a decline in labor productivity due to high temperature is reflected in declines in output and/or increases in labor costs. If the outdoor heat index HIis less than the critical value HI_c there is no impact on productivity and/or labor costs. If, however, HI > HI_c, then we would expect labor productivity to decline. We note that this heat index extreme, HI_c, is crop and geographically specific because there are crops that are more labor intensive than others and temperatures vary across regions. We expand on this notion in Section 2.6. The contextual nature of the impact of temperature on labor productivity enables us to pose two general hypotheses:

 Temperature impacts on agricultural labor productivity or crop production should be higher for labor‐intensive crops.

 The negative impact of temperature on labor productivity should occur for relatively high heat index values.