Climate Change and GDP

Professor: Erin Mayfield

Winter 2023

PROMPT

The relationship between climate variables (e.g., temperature, wind, precipitation) and economic outcomes (e.g., crop yields, industrial output, labor productivity) is well-supported by evidence. Understanding this relationship is crucial for predicting the monetary impact of expected climate change, and can aid decision-makers in both the public and private sectors in weighing the pros and cons of climate change mitigation measures.

In this analysis, I am using a cleaned and sorted "Historical.csv" dataset to perform a pairwise comparison between the historical climatic variables of temperature and precipitation, and the gross domestic product (GDP) per capita for 146 countries from the years 1961 to 2013.

In these scatterplots, historical changes in Gross Domestic Product (GDP) in relation to temperature and precipitation are shown. Additionally, a regression line is shown representing the relationship between these environmental factors and GDP.

The modeling approach here is to visualize the relationship between GDP and temperature and precipitation. The model formulation is a scatter plot with GDP as the dependent variable on the y-axis and temperature and precipitation as the independent variables. The point color is used to represent precipitation, with blue representing low values and red representing high values.

Based on this visualization, GDP per capita appears to decrease as temperature increases. However, it is not immediately clear from this visualization if precipitation has an effect on GDP per capita

This scatterplot shows temperature on the x-axis against precipitation on the y-axis and color codes the points based on their corresponding GDP per capita value, with a higher GDP per capita indicated by a darker-red, and a lower GDP per capita indicated by a lighter-red.

POINTS FOR FURTHER ANALYSIS

Analysis of the relationship between climate and GDP by industry or sector: The impact of climate on GDP may vary by industry or sector. Certain sectors such as agriculture, tourism, or energy may be more liable to changes in temperature, precipitation, and other climate factors than others. By separating these sectors, we may be able to identify more specific economic trends caused by climate change and therefore provide a more robust analysis of the relationship between climate, GDP, and other socioeconomic factors.

Data on adaptation and climate control measures: The negative effect of climate change on GDP may be mitigated by adaptation measures such as investment in infrastructure, development of new technologies, and changes in land use patterns. Including data on these measures, including, for example, how much money money has been devoted to climate change in each country historically versus how much is planned in the future, may help provide a more complete understanding of the relationship between climate and GDP.
Data on the distribution of the effects of climate on GDP: The impact of climate on GDP may not be evenly distributed within a country, either spatially or across population groups. Incorporating data on the distribution of the effects of climate on GDP may help to better understand the implications of climate change for economic inequality and poverty. In addition to GDP, it may be useful to look into more nuanced aspects of the overall economic wellbeing of each country and the effect climate change has on this. For example, we may also want to look at unemployment rates, average income, and inflation indices and how climate change may have a regional-effect on each of these factors. This may give us a more extensive understanding of the effects climate change will have on some of the more specific aspects of the economy that inevitably effect GDP.

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