Autologous Country Vector (ACV)

Autologous Country Vector (ACV)

ACV reference points capture the majority of world countries; approximating 79% of total world population, 18% OECD countries; and a representative spread of GNI per capita; roughly, 19% high income countries, 43% high-middle income countries and 38% low-middle income countries.

The Autologous Country Vector (ACV) (country composite index shown above) is constructed as a composite index (equation a) of the generalised additive model form (equation b) which synchronises to a concept of formulative duration world model (shown at Figure 1).

The structural form of the ACV is nested in a matrix solution set (equation c) that is contingent to the country vector set (equation d) and which fully reconciles with the coincident theoretical framework (Table 1) premised on applied theories of Cartesian mathematics, organic process, policy articulation, and country vector.

The magnitude of country vector is given by composite index components of: C1: country level (equation e), C2: country gradient (equation f); and C3: country momentum (equation g). These components capture statistical propensities of sample dependence (country level), system of distribution functions (country gradient), and transition probability (country momentum).

Transitivity within the ‘formulative duration world model’ denotes horizontal variance in the data envelopment analysis (DEA) concept (Despotsis, 2005), and invokes statistical ‘survivor models’ (Cox, 1972), namely, the hazard function and effect parameters of the proportional hazards model. In this direction, empirical data in the logic of complexity discerns that country experience of hazards is principally affected by the prevalence of policy entrepreneurs capable of seizing ‘windows of opportunity’, and external inter-dependencies that yield to a democratic peace ‘proposition’ (Braumoeller, 2003); as well as the possibility of a ‘switching point’ between two regimes (Quandt, 1958). Formulative duration may also be explained such that transitivity effectively normalises the uncertainty in Uncertainty Analysis (Saisana, 2005) while at the same it time fully actualises the sensitivity in Sensitivity Analysis (ibid).

Transformation Indices

Even while e-governments pursue both (i) organisational transformation, such as administrative and efficiency enhancements; and (ii) cultural transformation, by strategies such as One-Stop-Shops, marketing and outreach programs, and high volume transaction services (OECD, 2009), the omniscience of country momentum persistently accrues transformational value from dynamic and systemic processes. Specifically, the ACV may be deconstructed into constituent components for determination of the nested transformation indices: (i) dynamism index, represented by the premium of economic freedom above total public sector delivery, given by the equation DYI=EFWI-eWGI; and (ii) momentum index, indicating the residual vigour of institutions, a transposition of public integrity that is the inverse of entropic processes, indicated by the formula Auti={(DIPP + (1-eCPI)/2)}, where Auti refers to residual autonomy, and the term 1-eCPI denotes the inverse of the corruption perception index which is itself notionally in contrariety (cf. Transformation Charts below).