This thesis compiles five papers that independently cover issues on multifunctional forest, migration and climate change. Paper I addresses these questions: What is the effect of site quality on forest growth rate and variability in forest growth? How does site quality impact on ecosystem services, that is, timber production and carbon sequestration? Site quality indicator was found to positively affect forest growth and growth rate, and decreases uncertainty in the productivity. Using dynamic optimization model, Paper II estimates the economic value of site quality taking into account its interaction with timber value and carbon sequestration in Swedish forest. Analytical results showed that net present value when considering ecosystem services provided by the forest and its interaction with site quality is higher than in the case without site quality interaction. Paper III links educational attainment to internal migration decisions with much on rural-urban perspective using Ghana as a case study. The effect of educational attainment on migration decisions in 2005/2006 for urban in-migrant was found to be higher than the effect for rural in-migrant, with its significance varying for the different stages of educational attainment. In absolute terms, whereas the effect of secondary educational attainment on migration decisions for urban in-migrant is higher than for rural in-migrant, the reverse holds for higher educational attainment during the period 2012/2013. Paper IV examines the effect of climate element on internal migration decisions using similar methods and data as for Paper III. Whereas temperature positively affects the probability to migrate, aridity index negatively affects migration decisions. Individuals tend to move to the rural areas relative to urban areas with an increase in precipitation and or a decrease in aridity. Paper V explores the effect of climate variability and socio-economic factors on the number of infectious disease patients in Sweden. Temperature showed a linear negative effect on the number of patients, but a non-linear relationship when winter temperature is used. Conversely, a positive effect of precipitation on the number of patients is found, with modest heterogeneity in the effect of climate variables on the number of patients across disease classifications observed. Socio-economic factors were found to correlate with number of patients. We found significant persistence in the number of infectious disease patients but found only temperature and income as dominant drivers in a dynamic model.