Identifying the Public Administration Reform Performance through the Lens of Provincial Competitiveness Index and GDP Per Capita in Vietnam ()
1. Introduction
Vietnam’s fast economic development and impressive growth of the past decade can be attributed to the successfully implemented public policies and internationally accepted public governance practices that its government has actively embarked right since the start of the public administration reform. The public administration reform (PAR) in Vietnam has been considered as an ambitious process that seeks the “rules by laws” within a centralized and centrally managed framework. Having been lasting for more than a decade until now, this PAR aims to lift the state governance up to a more efficiency level, and thereby to cater better public services to the people at large [1-3]. As the results, the whole economy of Vietnam has been functioning in a competitive mechanism, rather than being centrally planned one [4]. The organizational structure of state governance has become leaner and more efficient with the objective of unleashing the creativeness among the members [5]. Public officers and civil servants have been sent to the trainings and capacity-building on “the sense of responsibility” as well as awareness of “serving the people unconditionally”. There is no doubt that these PAR efforts have been contributing positively to the success of Vietnam’s economy miracles, overcoming the roadblocks, and narrowing the gap of difference in an emerging civic society of Vietnam [6].
In this context, there have been a number of studies on the public administration reform in Vietnam. Howeverthey are merely qualitative in nature with the traditional approach aiming to touch the surface, to describe the status-quo of PAR process or to identify the roadblock hurdles to the local economic development [3,4]. For that reason, there is a need to set more light on the PAR performance with a quantitative method. Specifically, this study is to be conducted to identify the causal relationship between public administration reform performance, provincial competitivenesses and the GDP per capita. The reasoning behind the above mentioned causality is that public administration reform performance should be measured on the bottom-line quantitative indicators. That is, it should give rise to the understanding of whether or not PAR process would bring the better-off to the provincial competitiveness and more welfare to the public in the form of per-capita GDP. Against all odds, these are important indicators, indirectly reflecting the so-called economic development for every province in a broad sense [7].
2. Data and Study Model
2.1. Data for the Study
Data on provincial competitiveness index (PCI) for the year of 2010 was taken from the PCI Vietnam. This independent entity investigated the provincially-based data to explain the from-province-to-province difference in terms of legal environments and public policy [8]. This type of index assisted in explaining why provinces of the same country are different from each other on the ground of economic growth and dynamic development, especially from the private sector. The provincial competitiveness index consists of the component sub-indices such as: Entry cost; Access to Land; Transparency; Time cost of regulatory compliance; Informal charges; proactivity of provincial leadership; Business support service; labor training; and legal institution [9].
Data on public administration reform performance, known as PAPI measurement for the year of 2010 were extracted from the United Nations Development Program’s recent study [5]. The PAPI score was used to identify the two main dimensions of PAR process: public administration reform services and public services delivery. These are two most important bottom-line dimensions which could be interpreted as the reflection of whether PAR process is successful in Vietnam [10]. Meanwhile, the data on per capita GDP for the year of 2010, measured in US dollar terms were taken from respective provincial web-site or Committee for Ethnic Minorities, a ministerrial level agency under the Government [11].
2.2. Study Model
To quantify the causality relationships between GDP per capita and PAR performance index as well as the provincial competitiveness sub-indices, the following econometric model was adopted in this study:
(1)
where:
is natural logarithm of the GDP per capita for province ith;
is the vector of PAR sub-indices from 1st to jth for province ith;
is the vector of provincial competitiveness sub-indices from 1st to kth for province ith;
is residual term in the model.
The above-mentioned econometric model adopted in this study has obtained the two-pronged objectives. Firstly, it allowed the quantification of the causal linkages between the GDP per capita as dependent variable and the provincial competitiveness sub-indices and public administration reform performance indices as independent variables. Secondly, the model also overcame the normality condition or statistical normality test known as KomogorovSmirnov test [12,13]. As it came to decide the number of independent variables as presented in more detail in the next section, the econometric Equation (1) could be expanded in the following form:
(2)
where:
is natural logarithm of the GDP per capita for province ith;
is the natural logarithm of legal institution subindex for the province ith;
is the natural logarithm of “proactivity of provincial leadership” sub-index for the province ith;
is the natural logarithm of “PAR services” sub-index for the province ith;
is the natural logarithm of “public services delivery” sub-index for the province ith;
is respective linear regression coefficients for PAR and PCI variables;
is the error terms in the model.
This was the final econometric equation to be used for testing the causality linkages between the dependent and independent variables. The next section describes in more detail the extent to which the PAR performance and PCI sub-indices should exert a causal impact on the GDP per capita.
3. Data Analysis and the Findings
Data processing and analysis were carried out with the use of the SPSS 18 software. Due to the complexity of the provincial competitiveness index which consists of 9 subindices, factor analysis technique was used to condense them into a smaller and more meaningful number of variables [12]. These newly created factors would, on the one hand, facilitate the understanding of causality in question. On the other hand, they would allow the avoidance of multi-colinearity which could often be seen as a distortion of the “down-to-earth” causality relationship in the econometric equation. Table 1 presents the result of the factor analysis of the 9 provincial competitiveness subindices mentioned above. It shows that two new factors were identified and created with the statistically signifycant level. Below is the detailed description.
The first factor was composed of four sub-indices which attained high loading coefficients of 0.86, and 0.82, and 0.78, and 0.78, all exceeding the conservative cut-off point of 0.5. Thus, on the basis of the nature of PCI subindex scores, this factor was labeled as legal institutions with the biggest factor loading. Table 1 also reveals that the internal consistency for this factor was assured with the Cronbach Alpha reliability of 0.86, exceeding the Kaiser’s threshold of 0.7 [12]. The average scores of these four sub-indices reflected the degree of the legal matters, thus serving as a basis for creating a “legal institution” variable for hypothesis testing on a later stage.
By the same token, the second factor was identified with high loading coefficients for Proactivity of provincial leadership; Entry costs; Informal charges; Transparency and access to information; Time cost of regulatory compliance; as well as the dynamic leadership. The sec-
Table 1. Factor analysis of 2010 provincial competitiveness sub-indices.
ond factor possessed Eigenvalue of 2.19 and Cronbach Alpha reliability of 0.79 which satisfied the threshold of 0.7. The second factor was named as “provincial dynamism” on the basis of the item with the highest loading coefficient. The average score of the PCI sub-index scores would be used as a new variable in the model. Both these newly created factors accounted for a relatively high cumulative variance of 65% and satisfied the conditions imposed by the factor analysis technique.
To set more light on the question of whether provinces with high PAPI score can be highly linked to high PCI score, Pearson correlation was used with the findings to be presented in the Figure 1. It reaches the correlation degree of 0.45 and shows that the provinces such as Ho Chi Minh city, Phu Yen, Ha Tinh; Da Nang and Binh Phuoc are the ones with a positive correlation between public administration effort and PCI score. In the mean time, the provinces such as Kon Tum, Lai Chau, Dak Lak, Yen Bai, Quang Tri; Kien Giang and Tien Giang maintain a low degree of correlation between PAPI and PCI.
Similarly, the correlation between the PAPI and GDP per capita was presented below in the Figure 2. The public administration performance was positively correlated with per capita GDP at a close level of 0.6. Such cities as Ho Chi Minh, Da Nang, Dong Nai; and Hai Phong are the ones that were ranked as the highest in terms of public administration reform performance and GDP per capita. The capital of Ha Noi maintained a high level of GDP average. However, it came as a surprise that the heart of the country fell into the group with lowest PAPI score. The group of such provinces as Dak Lak; Lai Chau; Cao Bang; Yen Bai and Dien Bien is mountainous and poor. Understandably, they reached a level of low PAPI score with an exception of Phu Tho province which reached a high level of PAPI score as shown in Figure 2.
Table 2 presents the results of the log linear regression which was adopted to study the causal linkages between dependent variable on GDP per capita and independent variables in terms of public administration reform performance and provincial competitiveness.