Factors affecting worldwide deforestation rates

1. Factors affecting worldwide deforestation rates Howard Weir hw3632a@student.american.edu American University School of International Service

2. Research Question & Research hypothesis • What are some of the factors influencing deforestation rates around the world? • Research hypothesis: Deforestation rates are correlated to wealth, education and agricultural activity.

3. Background Information • Global Forest Land Use Change 1990-20051 • Purpose: To track worldwide deforestation rates • Findings : Deforestation is ongoing and is occurring most rapidly in tropical regions • Temporal Fluctuations in Amazonian Deforestation Rates2 • Theory: 10 variables (looking at agricultural and economic factors) are correlated to seasonal deforestation in the Amazon • Findings : Though the deforestation rate varied significantly over the studied time period, none of the 10 variables showed strong correlation with deforestation rates. • Theoretical and empirical gaps in the existing literature • Theoretical gaps: There are very few studies attempting to correlate deforestation with other factors. • Empirical gaps: The theoretical gaps are likely due to the lack of data on deforestation rates. 1: FAO, 2010. Global Forest Land Use Change 1990-2005. FAO Forestry Paper. 2: Ewers, R. M., Laurance, W. F., & Souza, C. M. (2008). Temporal fluctuations in Amazonian deforestation rates. Environmental Conservation, 35(4), 303.

4. Data • Unit of analysis/study : Countries • Source of the data: The data come from the World Development Indicators provided by the World Bank • Reliability of the data: The data contain observations for 209 countries, however the data are unevenly distributed and sometimes incomplete across the time series from 1990-2010. Forest coverage is in 5 year intervals, whereas other variables are assessed either more or less frequently. • Dependent variable • Forest coverage, given as a percentage of a country’s total land area. • Independent Variables • GDP per capita, given in year 2000 dollars • Live stock production index (1999-2001) = 100 • Number of Pupils in Secondary Education

5. Descriptive Statistics Table • The histogram shows that the distribution of the dependent variable (forest coverage) is heavily skewed to the left due to a large number of countries with either no forest coverage or very little coverage. • The mean of 32.11% with a standard deviation of 24 suggests the mean is a poor indicator of central tendency. • Forest coverage has significantly fewer observations than the other variables because the most complete studies on deforestation rates only track changes in 5 year intervals.

6. Descriptive Statistics

7. Correlation analysis of dependent variable

8. Regression Analysis – Dependent Variable is % forest coverage of total land area By looking at the models, we can see that GDP per capita, Livestock production and the number of Secondary education pupils are all statistically significant with regards to forest coverage (p<.05). Model 4 appears to be the best fit, offering the highest number of significant variables without adding insignificant ones. The R2 value tells us that 8.2% of the change in % forest coverage can be described by Model 4. For GDP per capita, we can say that an increase of $1000 correlates to a 22.3% increase in forest coverage For Secondary education pupils, an increase in 100,000 students in secondary education correlates to a 8.39% increase in forest coverage For livestock production, a decreasing index relative to 1999-2001 results in an increase in forest coverage.

9. Findings & Policy Implications of the research • Findings: • Wealthand agricultural activity are weakly correlated with deforestation. Correlation with education is less clear, in the regression model the relationship appears significant but the correlation analysis says otherwise. • Though the relationships are significant, these 3 variables explain just 8.2% of the variation in Forest coverage. More comprehensive data on deforestation rates is necessary in order to perform a more detailed study. • Policy Implications: • There are many factors affecting deforestation which means there is no single action that can be taken to preserve forests. Instead forest conservation should be approached in a holistic manner, seeking to address many factors simultaneously.