The impact of climate change on fertility^*

In this section, we discuss how climate change may alter fertility via different economic channels. Clearly, non-economic factors, especially cultural norms, have important consequences for fertility decisions [18, 19]. It is unclear, however, how climate change might affect cultural norms over the relevant time horizons. Thus, we leave the role of cultural evolution as an open question for future research.

In the economic approach to fertility, parents have a finite set of resources and preferences over various outcomes, as with any other decision. They use these resources to achieve the best possible outcome attainable within their economic constraints. In relation to fertility, the decision has two parts. First, individuals must decide the quantity of resources, both time and money, to devote to childrearing. Second, conditional on the total amount of resources devoted to childrearing, individuals must decide whether to use those resources to have more children or invest more in the future of each child. This latter decision is known as the quantity-quality trade-off. This simple model of choice delivers several insights. First, when the relative cost of having a child increases—either because the absolute cost of having a child increases or the cost of another activity decreases—the fertility rate will fall. Second, when the relative benefit of having another child decreases, then fertility will fall. Thus, the economic model of fertility suggests that climate change will affect fertility decisions by altering the relative costs and benefits of having children and investing in the well-being of each child.¹⁰

Effects through structural transformation

Potential impacts outside of structural transformation

As discussed above, there are many mechanisms that will determine the full strength of the effect of climate change on fertility. We now turn to a examination of one particular mechanism, the interaction of structural transformation and the quantity-quality trade-off. Our goal with this modeling exploration is not to provide a full quantitative accounting of the effects of climate change on demographic outcomes. Instead, by showing the importance of one mechanism, we demonstrate that climate impacts are likely to be substantial, highlighting the need to future research. We also highlight important sources of heterogeneity that may exacerbate existing inequities.

Our model combines standard economic-demographic theory and empirical evidence on the consequences of climate change. We build on the standard overlapping generations (OLG) approach to endogenous fertility [26, 27, 52].¹¹ We follow individuals through two stages of life. In the first stage of life, they are children who consume parental time. In the second stage, they work, consume goods, and raise children. To capture the quantity-quality trade-off, we assume that parents have preferences over the lifetime earnings of children and that raising a skilled child uses more parental time than raising an unskilled child. Since skilled children earn higher wages, parents face a trade-off between quality and quantity.

We employ a two-sector model of structural transformation. There are two types of goods, agricultural and non-agricultural. Existing research shows that agriculture uses substantially less skilled labor per unit produced than does non-agricultural production [31, 32]. To simplify analysis, we assume non-agricultural work uses only skilled labor and agricultural work uses only unskilled labor.

Consistent with empirical evidence, we employ a model with low substitutability between the two types of goods, implying that workers reallocate towards more damaged sectors after a climate shock [22, 23]. Thus, if climate impacts lower the productivity of agricultural production, the scarcity of food leads to an increase in relative food prices. The increase in relative food prices then increases relative wage for agricultural work and lowers the incentive for parents to invest in child quality. As a result, fertility increases and educational attainment decreases. This is the economic mechanism through which climate change affects fertility and human capital in our model.

Our specification for climate damages comes from Desmet and Rossi-Hansberg [17]. These estimates capture the differential effect of climate change on agricultural and non-agricultural industries, as well as the spatial heterogeneity in the impacts of climate change. These estimates are particularly well suited to our application, because they were generated for a two-sector model similar to ours.¹²

Our focus is on the demographic effects of climate change, rather than the causes of climate change or the optimal policy response. Consequently, we consider the case of a small economy for which technological progress and global temperature can be taken as exogenous variables. In our primary analysis, we calibrate the model to match demographic features of Colombia. We also present results for Switzerland in the supplemental online material. To ensure that our base case is consistent with existing demographic projections used in climate change analysis, we calibrate our model to past demographic trends and the projections embodied in the Shared Socioeconomic Pathways [56]. Specifically, we calibrate the model to SSP2, which serves as a 'middle of the road' scenario.¹³ The model fit is evaluated in figure 1. The demographic projections show the usual trends for developing countries, increasing education and falling fertility. Despite its simplicity, our model captures these patterns well.

Zoom In Zoom Out Reset image size

We use the calibrated model to examine how demographic outcomes change when global temperature changes. Specifically, we examine how different levels of global mitigation will affect population dynamics by comparing demographic outcomes under different exogenous emissions paths given in the representative concentration pathways (RCPs) [58, 59]. Holding the underlying demographic parameters fixed, changes in emissions capture different global mitigation scenarios. Figure 2 presents the global carbon concentrations and temperature for Colombia under the different RCPs.

Zoom In Zoom Out Reset image size

Results

Figure 3 presents the results of the computational exercises, which are designed to better understand the effects of climate change on fertility via the quantity-quality trade-off and structural transformation. All results are shown relative to a baseline case with constant climate.

Zoom In Zoom Out Reset image size

Adaptation

The model captures how adaptation to climate change may include changes in fertility and human capital accumulation via structural transformation and the quantity-quality trade-off. We start by considering effects predicted for Colombia in its true location. We focus on RCP 8.5, a pessimistic scenario without strong mitigation policies. The temperature at 5° latitude will increase by 10% in the year 2100, compared to the baseline scenario with constant climate. The damage estimates imply that the relative productivity of the non-agricultural sector will increase by almost 45%.

As described above, this increases wages in the agricultural sector due to the low substitutability between consumption goods. Since agricultural production uses unskilled workers, this lowers the return to acquiring skill. The model suggests that ratio of skilled to unskilled children decreases by 15% compared to the baseline. The quantity-quality trade-off implies that fertility will rise when education falls. Consistent with the economic model, we measure fertility via the child-to-adult ratio. As education decreases, fertility increases, but then converges back to the baseline level. This convergence occurs because the baseline model predicts that developing countries will experience rapidly falling fertility independently of other forces (see figure 1). The model suggests that, in the long run, the total child population will be 1.35% higher due to the transitory changes in fertility. Overall, climate change leads to less education and greater fertility, when compared to a world with a constant climate.

Mitigation

The above results demonstrate that standard economic theory, when combined with existing estimates of the impact of climate change, predicts that changes in climate will affect fertility and human capital accumulation, when compared to a world with a constant climate. We now turn to investigating the role of mitigation policies. Holding the underlying economic-demographic model constant, we examine the effect of exogenous differences in mitigation policies, which result in differences in carbon concentrations.

The RCP 2.6 scenario represents a world with stringent mitigation policies and leads to a 3.3% higher temperature than the baseline scenario of a constant climate. Recall that temperatures were 10% higher in RCP 8.5. The ratio of non-agricultural productivity to agricultural productivity is 5% above baseline, instead of the 45% under RCP 8.5. The model suggests that this effect is too small to have a meaningful impact on skill accumulation, fertility or the size of the child population over the next 60 years. In other words, strict mitigation policies can essentially eliminate the demographic consequences of climate change at low latitudes, at least when restricting attention to the quantity-quality mechanism our model investigates.

Spatial heterogeneity

Figure 3 also illustrates the importance of spatial heterogeneity. We perform a computational experiment considering an economy identical to Colombia's, but at alternate latitudes. This experiment captures the heterogeneous effects of climate across latitudes, holding all else equal.

The effect of climate change on demographic outcomes differs substantially across latitudes. This occurs for two main reasons. First, the relationship between global and local temperature depends on latitude. Second, changes in temperature have non-linear effects on agricultural and non-agricultural productivity. As a result, both the direction and magnitude of the effect on differential productivities—which drives demographic outcomes—differ across latitudes.

We examine the results for an economy like Colombia that is located at 25° of latitude (figure 3). The effect of carbon concentrations on temperature are larger at this higher latitude. The effect on relative productivity, however, is smaller. As a result, the effect on fertility and skill accumulation is smaller, despite larger changes in temperature.

We also examine the effect of temperature on economic and demographic outcomes for an economy like Colombia at 45° of latitude (figure 3). In this case, higher temperatures increase the relative productivity of agriculture, pushing workers into other sectors and inducing parents to substitute toward child education. Thus, population decreases and skill acquisition increases as a result of climate change. The magnitudes are large. Under RCP 8.5, the ratio of skilled to unskilled children increases by almost 25% compared to the baseline, and the child population falls by 3%. Once again, lower carbon concentrations lead to smaller demographic impacts, but there are still meaningful changes under RCP 2.6.

Heterogeneity by levels of development

In the supplemental material, we re-calibrate the model and repeat all of the exercises for Switzerland, another small economy for which it is appropriate to take technology and atmospheric carbon dioxide concentrations as exogenous. Results for Switzerland illustrate how climate change might affect demographic outcomes in a richer country. Switzerland has both a higher ratio of skilled children and a lower fertility rate than Colombia. This is consistent with known demographic patterns in developed and developing countries and is well described by the calibrated model. We examine Switzerland at its true location (45° latitude), as well as alternate locations given in figure 3. By comparing the two different hypothetical countries at the same latitude, we can isolate the partial impact of development. The outcomes for Switzerland and Colombia are nearly identical at all latitudes, suggesting that location, rather than development, is the primary source of heterogeneity in the climate-fertility relationship captured by our model.

Our model suggests that damage from climate change for countries at low latitudes may be substantially larger than previously estimated. In particular, by changing the return to acquiring skills, climate change can induce parents to have more children and invest less in the education of each child. The increased damage from these channels implies larger benefits from mitigation policies. Fortunately, the model suggests that stringent mitigation policies can largely eliminate the impacts of climate change on fertility via the quantity-quality trade-off channel.

Our model also has implications for inequality. It is widely acknowledged that poor countries are less capable of adapting to climate change than rich countries [61, 62]. Our results highlight another potential source of spatial inequality in vulnerability to climate change: the differential effect of climate change on relative sectoral productivity will affect parental decisions about fertility levels and education for children. In high latitude countries, which tend to be richer, climate change may lead to lower fertility and higher skill accumulation, the reverse of what we find for low latitude countries. These forces may increase the income gap between the richer high-latitude countries and poorer equatorial countries. We find little heterogeneity in impacts when considering differences in levels of development independently of differences in location.

Our model focuses on a single channel. As a result, it is necessarily preliminary, and there are many ways that future work can build on our results to provide a more complete quantitative accounting of the impacts of climate change on demographic outcomes. Most immediately, future studies can quantify the other economic channels discussed in the earlier sections of this paper. Channels related to health are likely to be of particular importance. Future work could also combine our model with a realistic representation of international trade, since climate change alters patterns of comparative advantage [17].¹⁴ Moreover, our results suggest that foreign aid targeted to improve agricultural productivity or improve food availability might be effective at lessening the negative demographic consequences of climate change. Thus, further work could highlight the potential for international development assistance to bolster climate change adaptation. As discussed above, both cultural factors and large-scale disruptions, such as natural disasters and civil wars, can also be affected by climate change, resulting in significant impacts on fertility that may have interactions with the economic mechanisms discussed here. Future work can also expand on our results and discussion by considering non-economic mechanisms.

To understand the full impact of climate change and the benefits of mitigation policy, it is important to consider how adaptations to climate change may include demographic change. Our model suggests that demographic responses to climate change will increase damage in tropical countries and exacerbate existing inequities, increasing the benefit of mitigation policies. These results suggest a need for future work to build on our results by exploring and quantifying other important channels.

This project has received funding from the following sources:

• The European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 703399 for the project 'Robust Policy'.
• The European Research Council under the European Community's Programme 'Ideas'—Call identifier: ERC-2013-StG/ERC grant agreement n°336703- project RISICO 'Risk and uncertainty in developing and implementing climate change policies'.
• The Fund for Innovative Climate and Energy Research.
• The Canada Research Chairs program of the Social Sciences and Humanities Research Council of Canada.

The authors declare no conflict of interest.