Characteristics of Sample Provinces

Contexts in source publication

Context 1

... non-project provinces were selected based on their similarity with the project provinces in such factors as the existence of IPC, Gross Provincial Product (GPP) per capita, the share of the manufacturing sector in GPP, the number of SMEs, and the industrial structure within the province. 2 In particular, we relied on national statistics summarized in Table 1 and made an index, which is a sum of the GPP per capita, the share of the manufacturing sector in GPP, and the number of SMEs (all standardized). We ranked all the provinces by this index and chose several provinces which are close to the project provinces in terms of this ranking as well as geographical location. ...

Context 2

... we investigate whether these positive impacts are actually transmitted to SMEs to benefit their activities. Tables 8 through 12 Table 12. In our estimating equation, there are two sources of endogeneity: one is the use of BDS and the other is the status of intervention, i.e., being in the RISMEP province or not. ...

Context 3

... we investigate whether these positive impacts are actually transmitted to SMEs to benefit their activities. Tables 8 through 12 Table 12. In our estimating equation, there are two sources of endogeneity: one is the use of BDS and the other is the status of intervention, i.e., being in the RISMEP province or not. ...

Context 4

... we move on to examine whether the increased interactions between SMEs and BDS providers in RISMEP provinces shown thus far have yielded any results in improving SMEs' performances (Tables 10-12). Table 10 reports the average effect of the project while Management scores tend to be higher in RISMEP provinces in panel A, and we also find that BDS users in RISMEP provinces perform better than BDS users in control provinces in panel B (Column (1)). ...

Context 5

... we move on to examine whether the increased interactions between SMEs and BDS providers in RISMEP provinces shown thus far have yielded any results in improving SMEs' performances (Tables 10-12). Table 10 reports the average effect of the project while Management scores tend to be higher in RISMEP provinces in panel A, and we also find that BDS users in RISMEP provinces perform better than BDS users in control provinces in panel B (Column (1)). In magnitude, they tend to score about 0.7-0.8 points higher out of the total of 9 points. ...

Context 6

... the average number of permanent workers in 2013 was 21.6, the distribution is highly skewed to the right and the median is 9. Thus, we divided the sample into smaller SMEs (fewer than or equal to 9 permanent workers) and larger SMEs (more than or equal to 10 permanent workers) and conducted the previous analyses (Table 12). We find that the RISMEP project strengthened the network between BDS providers and SMEs for the smaller SMEs while it did not for the larger SMEs (Colums (1) and (7)). ...