Spatial heterogeneity, industry heterogeneity, and entrepreneurship

In Vietnam, in the early 1980s when private ownership has not yet gained full legitimacy and labor mobility across regions and professions was illegal, many private firms had a problem recruiting high-quality workers, although labor forces were abundant in most regions.

Surveyed enterprises are all enterprises regardless of their ownership forms and industries currently operating under the stipulation of the Law on State-owned Enterprises, Law on Cooperatives, New Enterprise Law, and Law on Foreign Investment, which include enterprises operating on seasonal contracts; enterprises temporarily closing down for innovation, expansion or refurbishment; enterprises temporarily closing down for merger and acquisition. The list of surveyed enterprises is constructed mainly based on three sources: (i) the list of surveyed enterprises from the preceding year; (ii) records from the tax department; (iii) records of new business registrations from all administrative levels (commune, ward, district, provincial level). The first source is to ascertain that all previously surveyed firms are followed up consecutively, while the latter two sources are to take into account new entrants/start-ups. Thus, they survey does reliably measure entrepreneurship when both new entrants and incumbents are tracked throughout their life.

Despite these data limitations, we still claim that our data are still able to capture the entrepreneurial spirit of necessity entrepreneurship in Vietnam because: first, knowledge and data of the informal economy are extremely limited, based solely on case studies and small unrepresentative surveys. The only statistically representative data available concerned household businesses in general drawn from the GSO census data (Tien Cuong et al. 2008) which we are using for this paper. Second, the informal sector plays a very limited role to the formal sector and the overall economy. Purchases from and sales to the formal sector are only marginal within its main market of households and household businesses. Third, necessity entrepreneurs (the survivors) take up only 39% of informal businesses, the remaining, resourceful (51%) and professionals (10%) are the high-end groups driven by exploring viable opportunities but want to escape from time-consuming and complex red tapes. Thus, informality does not differentiate necessity-driven from opportunity-driven entrepreneurship. Fourth, informal status just reflects the initial start-up stage of new entrants. Once they get over the survival challenges, they move from informal to formal status to obtain benefits from formality such as providing more opportunities on receiving government assistance. Therefore, informality somewhat reflects ‘entry mistakes’ rather than ‘entrepreneurial capital’ of Vietnam (Tenev et al. 2003; Cling et al. 2011; Nguyen et al. 2013).

Despite the official recognition of the private sector within the Vietnamese economy, the growth of the private sector was still lower than that of the state-owned sector during 1991–2000. The output share of the private sector in industries reduced from 26.7% in 1991 to 21.6% in 2000. This was due to the requirement of a large number of licenses before actual business operations, the difficulty in accessing credit and lands, and due to the slow progress of equitization of SOEs. Since 2000, a significant increase in the number of firm entries has been evident due to the implementation of several favorable institutional restructuring measures. Particularly, the private entrepreneurship surged significantly just after the enactment of Law on Enterprise in 2000 and the signing of the bilateral agreement between the USA and Vietnam in 2001. Statistical data showed that the number of registered private enterprises in 3 years 2001–2004 was equivalent to the total registered ones during the 1990s. Together with Vietnam’s joining WTO in 2007, the number of new firms in the period 2005–2010 was more than twice the increase in the 2000–2004 period. Many private enterprises penetrated into heavy industries which had previously been the playing field of large SOEs only, such as production of steel, cement, electricity. Consequently, the output share of the private sector increased up to 38.8% in 2005.

One advantage of using the gross entry rate instead of the net entry rate as a measure of entrepreneurship is that region–industry units are comparable, despite the huge difference in the region and industry sizes. Further, net entry fails to capture the dynamics of firm start-up and firm exit. That is, given the number of gross entries, the net entry measure will increase as the number of exits from the industry decreases. Because the pattern of industry exits varies across industries, the extent to which net entry deviates from actual gross entry also varies substantially from industry to industry (Audretsch 1995).

It should be noted that changes in demand within the niches in an industry may not be captured by the industry-level growth, since it is possible that niches within an industry experience tremendous variability in sales without causing any changes in the overall industry demand, especially when one niche is growing significantly while another is shrinking. From this perspective, niche-level dynamism is a crucial factor which encourages entrepreneurship by creating opportunities in segmented markets. To measure niche-level dynamism, following Li (2016) for each two-digit SIC industry, we first identify the three-digit SIC sector with the largest sales and then compute the absolute value of the changes in the percentage of the industry’s sales from each year to 2010.

\(F(1, 593) = 2.639\).

\(\hbox {Prob} > F = 0.1048\).

Although our dataset could not cover the whole informal sector in Vietnam, but as we discussed above, it does take into account a part of the informal sector by surveying registered (household) private businesses and following up their development over time. On the other hand, necessity entrepreneurs (the survivors) take up only 39% of informal businesses which actually play a limited role to the economic growth of the country.

In statistics, the Bayesian information criterion (BIC) or Schwarz criterion is a criterion for model selection among a finite set of models; the model with the lowest BIC is preferred. It is based, in part, on the likelihood function. For our two models, we found a smaller BIC for the GMM model: BIC\(_\mathrm{negative\,binomial} = 3086.319\) and BIC\(_\mathrm{GMM} =657.408\)