Empirical Analysis Clause Samples
Empirical Analysis. THE GAP APPROACH The data collected by the ENVIPOLCON project describe the development in the period 1970 – 2000 for 40 environmental policy issues in 21 European countries plus – for reasons of comparison – the USA, Mexico and Japan. The policy issues cover the whole range of environmental problems (air, water, waste, noise, energy and climate, nature protection, etc.). Moreover, 682 Journal of European Public Policy the list includes policies relating to tradable products and production processes as well as procedural measures such as environmental impact assessment or eco- labelling. Finally, there are policies which have become subject to international regulation at any point in time during the period 1970 – 2000 and policies which have not. The data were collected by way of detailed questionnaires filled in by established experts in the respective countries and carefully checked and double-checked for completeness and comparability by the project team (▇▇▇▇▇▇▇ et al. 2008). For this paper, two types of data were used: Downloaded by [Radboud Universiteit Nijmegen] at 04:52 09 July 2012
Empirical Analysis. The nature of the data implies a need for either a fixed effects model or a random effects model. This is due to the fact that the data is in the form of panel data. While a pooled ordinary least squares (OLS) model may also be utilized for panel data, a pooled OLS requires the assumption that there are no unique variable characteristics of the entities in the data set. School districts do have unique characteristics that vary and therefore, I cannot use a pooled OLS for the panel data in this study. Thus, instead, I consider only a fixed effect model and a random effects model. 𝐷𝑟𝑜𝑝𝑜𝑢𝑡𝑖𝑡 = 𝛽1 𝑂𝑛𝑒𝑌𝑒𝑎𝑟𝑈𝑛𝑑𝑒𝑟𝐿𝑎𝑤1,𝑖𝑡 + 𝛽2 𝑇𝑤𝑜𝑌𝑒𝑎𝑟𝑠𝑈𝑛𝑑𝑒𝑟𝐿𝑎𝑤2,𝑖𝑡 + 𝛽3𝑋3,𝑖𝑡 + 𝛼𝑖𝑡 + 𝑢𝑖𝑡 where 𝐷𝑟𝑜𝑝𝑜𝑢𝑡𝑖𝑡 represents one of the dependent variables in question, as described in Section 3A, 𝑂𝑛𝑒𝑌𝑒��𝑟𝑈𝑛𝑑𝑒𝑟𝐿𝑎𝑤𝑖𝑡 and 𝑇𝑤𝑜𝑌𝑒𝑎𝑟𝑠𝑈𝑛𝑑𝑒𝑟𝐿𝑎𝑤𝑖𝑡 represent the independent variables in question, 𝑋3,𝑖𝑡 represents a vector of explanatory variables utilized as control variables, 𝛼𝑖𝑡 represents the unknown intercept for each entity, and 𝑢𝑖𝑡 represents the error term. 𝑂𝑛𝑒𝑌𝑒𝑎𝑟𝑈𝑛𝑑𝑒𝑟𝐿𝑎𝑤1,𝑖𝑡 and 𝑇𝑤𝑜𝑌𝑒𝑎𝑟𝑠𝑈𝑛𝑑𝑒𝑟𝐿𝑎𝑤2,𝑖𝑡 are dummy variables. While fixed effects is useful to this study due to the nature of the data, it is important to note that fixed effects may not be a flawless model for this study. This is mostly due to the fact that fixed effects models are not the best choice for variables that change slowly over time. Dropout can be considered a slowly changing variable and therefore, there are some limitations with the use of a fixed effects model in this study. Despite this limitation, we find that a fixed effects model is still a superior choice to a random effects model for this particular study. I also consider a random effects model for this study, which is represented by the equation: 𝐷𝑟𝑜𝑝𝑜𝑢𝑡𝑖𝑡 = 𝛽1 𝑍𝑒𝑟𝑜𝑌𝑒𝑎𝑟𝑠𝑈𝑛𝑑𝑒𝑟𝐿𝑎𝑤1,𝑖𝑡 + 𝛽2 𝑂𝑛𝑒𝑌𝑒𝑎𝑟𝑈𝑛𝑑𝑒𝑟𝐿𝑎𝑤2,𝑖𝑡 + 𝛽3 𝑇𝑤𝑜𝑌𝑒𝑎𝑟𝑠𝑈𝑛𝑑𝑒𝑟𝐿𝑎𝑤3,𝑖𝑡 + 𝛽4𝑋4,𝑖𝑡 + 𝛼 + 𝑢𝑖𝑡 + 𝜀𝑖𝑡 where 𝐷𝑟𝑜𝑝𝑜𝑢𝑡𝑖𝑡 represents one of the dependent variables in question, as described in Section 3A, 𝑍𝑒𝑟𝑜𝑌𝑒𝑎𝑟𝑠𝑈𝑛𝑑𝑒𝑟𝐿𝑎𝑤1,𝑖𝑡, 𝑂𝑛𝑒𝑌𝑒𝑎𝑟𝑈𝑛𝑑𝑒𝑟𝐿𝑎𝑤2,𝑖𝑡, and 𝑇𝑤𝑜𝑌𝑒𝑎𝑟𝑠𝑈𝑛𝑑𝑒𝑟𝐿𝑎𝑤3,𝑖𝑡 represent the independent variables in question, 𝑋4,𝑖𝑡 represents a vector of explanatory variables utilized as control variables, 𝛼 represents the unknown intercept, 𝑢𝑖𝑡 represents between-entity error, and 𝜀𝑖𝑡 represents the within-entity error. 𝑍𝑒𝑟𝑜𝑌𝑒𝑎𝑟𝑠𝑈𝑛𝑑𝑒𝑟𝐿��𝑤1,𝑖𝑡, 𝑂𝑛𝑒𝑌𝑒𝑎𝑟𝑈𝑛𝑑𝑒𝑟𝐿𝑎𝑤2,𝑖𝑡, and 𝑇𝑤𝑜𝑌𝑒𝑎𝑟𝑠𝑈��𝑑𝑒𝑟𝐿𝑎𝑤3,𝑖𝑡 are dummy variables. Random effects models rely on the assumption that any unique characteristic variation among entities is uncorrelated ...
Empirical Analysis. In this section I will report the results from the proposed nonhomogeneous Hidden Markov Model together with a static model which did not consider the relationship dynamics between players and the mobile application. I will especially focus on the part of results concerning my three research questions on points pressure, Gambler’s fallacy and Hot-hand, and the impact of social status.
Empirical Analysis