Forests and Human Development: An Analysis of the Socio-Economic Factors Affecting Global Forest Area Changes(<Special Issue>FORCOM 2011)

Abstract

Aii Analysis of the Socio-Economic Affecting Global Forest Area Changes 'Ibtsuya Michinaka 'iandMotoe Miyamoto '2 msSIRAcr This study examined the impacts ot socio-economic factors on forest area change by human development 1ffvel of countries. Cluster analysis and panel data analysis were combined to solve the problem of heterogeneity in panel data analysis and the problem ef data availability to some extent, The results show that many soci}economic factors have negative impacts on forest area in counhies at low levels of human develepment, but their impacts become positive in countries at higher levels of human development, such as rate ef rural population, adult literacy rate, and GDP per capita. The findings ot this research remind decision makers to pay attention to increasing countries' level of human development when atternpting te prevent deforestation, because people in higher human development index countries tend to be more protective offorests. Kleytvonts: human development, socio-economic factors, deforestation, cluster analysis, panel data analysis INIIIODUenON People treat forests differently at different stages of human development. These diflerences can be seen throughout theusands of years of httman history and in changes in forest area ever the past twe decades in counnies at different stages ofdevelopment, Global forest area has been decreasing, Although the pace of this decline has slowed, 83 million ha of forest disappeared from 1990 to 2000, and 52 millien ha of forest were eliminated between 2000 and 2elO, according te FRA2010 (FAO, 201e). The countries with the largest decreases in forest area in the past two decades include Bruzil (55.3 million ha), Indonesia (24.1 million ha), Nigeria (8.2 mi11ien ha) and Tbuizania (8.1 million ha) . Of the 233 countries and regions Iisted in FRA2010, forest area decreased in 88 countries and increased or remained stable in 136 countries (forest area data are not available tor remaining countries). Numerous studies have examined the relationship between forest resources and socio-econemic factors, from macro-level analyses utilizing multinational data to micro-level analyses based on field investigations. In particular, poverty (er ecenomic level) and

Factors Affecting Forest Area Changes in Cambodia: An Econometric Approach

“…Population is a factor that is considered in most socio-economic analysises (Michinaka & Miyamoto, 2013). We use the total population, which represents the size or magnitude of the population.…”

Forecasting Forest Areas in Myanmar Based on Socioeconomic Factors

“…Deforestation is mainly the result of human behavior due to specific socioeconomic circumstances. The roles that people play regarding forests in a country may vary when their socioeconomic circumstances change [20]. Many researchers use per capita GDP or income to reflect socioeconomic development; however, demographers have also found a population growth transition during the process of socioeconomic development in many countries and regions and have proposed a population transition theory [59,60].…”

“…Panel data analysis, an econometrics approach, was adopted in the research. Panel data analysis has been widely used in analyzing deforestation issues (e.g., [20,30,31,47]). For developing countries, long time-series data are usually not available.…”

Approximating Forest Resource Dynamics in Peninsular Malaysia Using Parametric and Nonparametric Models, and Its Implications for Establishing Forest Reference (Emission) Levels under REDD+

“…Herold et al [20] and Gutman and Aguilar-Amuchastegui [21] identified three types of approaches to the establishment of a REDD+ reference level: the strictly historical approach, adjusted historical approach, and simulation models. Although forest transition theory proposes a simple model showing the pattern of forest cover changes over time, many other drivers have also been analyzed, including distance to roads and markets [22], fallow and cropping lengths [23], cultivated area [24], wood scarcity [25], land rent [7], historical deforestation, forest cover, per capita GDP, agricultural GDP, human population, road network [20], human development [26], and rural and urban populations [27], to name a few. Analysis methods have included simple regression, multiple regression, and non-linear regression at household, sub-national or national levels.…”

“…However, here we argue that, due to its availability, FAO data is still a valid choice. Michinaka and Miyamoto [26] used FAO and UNDP data in cluster and panel data analyses to evaluate forest area changes in relating to life expectancy at birth, adult literacy rate, per capita GDP, total human population, rural population rate, and agriculture GDP in 205 countries. These authors found several factors that negatively impact forest area in countries with low human development levels, but these impacts become positive in countries with higher human development levels.…”