Another problem occurs as the scope of the regression is decreased. Data In this section the data used in the study are described, as well as the data sources and information that could be relevant for related work.
This issue of lag time and temporal scale is one which needs to be investigated better and used to select better proxy variables in future studies. In this figure, windspeed is used as the vertical axis. Analogous to the maps generated for the Africa-wide regression, Figure 16 presents the share of soil degradation of poverty inducing factors in Ghana.
As a first step, we deal with the confounding problem by including a set of country-level covariates contained in vector C2ct, as in specification 2 below. Therefore, statistical analysis performed on the dataset may recover true relationships between explanatory variables and soil degradation, but it is also possible that it will simply recover the modelling and assumptions that were put into GLASOD development.
It is tempting to use the wealth of relevant, but endogenous, variables such as yields, fertilizer imports and traction measures. The home environment is considered the main contributor to SES reading outcomes. In this case, the spatial autocorrelation corrections should not be used because they confound the hypothesis tests with the endogenous variables.
For example, while changes in the terms of trade of a country certainly have implications for the socio-economic status of its population, it is problematic as a proxy for welfare, as the effects of changes in terms of trade on welfare will vary by the types and amounts of goods exchanged on international markets, and the degree to which domestically produced substitutes are available as well as the distribution of the population engaged in market transactions affected by international prices.
The existence of these data was critical as it is difficult to obtain comprehensive GIS data at a subnational level for most nations.