Regression model 1 and results

Multivariate analysis is applied to explore the correlates of a wide range of factors—within the overall business, investment and institutional environment—of job creation. The analysis is conducted using ordinary least squares (OLS) regressions, which is the standard approach in the literature analysing job growth using enterprise surveys (see for example: Rutkowski 2003; Ayyagari et al. 2011; Dutz et al. 2011). The dependent variable is the average annualised job growth rate of firms over the past three fiscal years (as defined earlier). With job growth expressed here in annual percentage terms (not in log), it is possible to interpret estimated coefficients as the change in the percentage job growth rate relative to a unit increase in the regressor. The selection of independent variables for the models has been in part influenced by previous papers that identify relevant correlates of employment growth in other regions and globally—in particular, Fox and Oviedo (2008), Pagés et al. (2007), Dutz et al. (2011), and Shi and Michelitsch (2012). Incorporating various variables identified as important in these papers simultaneously and also including a number of additional variables identified as relevant in the descriptive results earlier, the paper here attempts to reduce levels of omitted variable bias15. The independent variables analysed here range from initial level of employment in the base year and other basic firm-level traits (such as age and location) to sector of activity (manufacturing, services and other sectors), wage and productivity levels, technology and infrastructure (email use, exports and electricity), business regulation and finance, as well as corruption, among other factors.

Yet in contrast to the papers listed above that run cross-country pooled regressions, this paper explores the correlates of job growth in each country individually—with the advantages of this approach outlined in the introduction. Interpreting econometric results is also generally easier in single country regressions as outcomes are linked to country specific circumstances. Because the regressions are conducted for each country, the main value is in comparing the correlates of specific firm traits and endowments within a country, not between countries—while across countries it can be useful to identify trends and assess whether a variable’s correlate is consistently negative or positive and consistently significant.

Before presenting the results it is important—while not common practice in research—to outline the limitations of firm-level analyses, with the strong constraints of enterprise survey data already outlined in Section 2. In terms of unobserved factors in such analyses, a number of (especially non-firm level) variables can influence job creation that are not included in the firm-level enterprise survey data and thus in the regression models. The explanatory power of the model specification is thus not particularly high for a few countries such as the Philippines, for example, at 0.10. These unobserved factors can include the rule of law, governance, labour regulations, firms’ specific hiring and firing costs, and macroeconomic variables such as inflation, per capita income and economic output. They can also include occupational decisions made in households and social norms about employment. In particular, fertility rates and dependency ratios can largely drive employment growth in the longer-term (see e.g. World Bank 2012), which cannot be controlled for using firm-level survey data. Such factors can be important as they can potentially influence firms differently across different regions within a country. Yet data at the sub-national level for many such factors are often difficult to obtain and data are not merged from other sources (for those variables where data exist) into the enterprise-level dataset used here. This would require a number of important assumptions given different data collection methodologies, data collected at different times of the year from different sources with different time-lags etc. Such omitted variables can be a limitation as they (such as fertility rates, for example) can be correlated at times with independent variables (such as firm size or city size, for example) so that there may likely be a correlation between the error term and independent variables. This paper instead takes a particular focus on exploring specific enterprise-level factors that can possibly influence job creation in the shorter-term, i.e. over a three year period.

It is important to also note that endogeneity affects all analyses using enterprise survey data16. To try and reduce further levels of measurement error and endogeneity, the models applied here do not include subjective measures as variables (such as firm perceptions of whether access to finance is a major constraint) but rather only objective measures are used (such as actual information on whether a firm has a credit line or loan). An example is that it is more likely for successful entrepreneurs (whose firms grew) to view the business climate as having fewer constraints compared to those with less success (i.e. a potential frame-of-reference bias). Another example is that it is conceivable that many firms will complain about levels of taxation as a constraint, while they may not weigh the social benefits (e.g. skill levels of their employees) and economic benefits (e.g. road and port infrastructure to move their products) associated with taxation that they and society receive. There is also the issue of latent heterogeneity in personality traits of firm owners. Many firm-level econometric analyses nonetheless include subjective indicators in their models (see e.g. Beck et al. 2005; Ayyagari et al. 2008; Carlin and Schaffer 2012).

Results for model 1 are presented in the following. Table 3 illustrates that micro and small firms can be a strong and consistent correlate of employment growth across individual East Asian and Pacific countries. Initial firm size at the baseline year (three fiscal years ago) is used here instead of current firm size to reduce levels of endogeneity related to firm growth over this period. In an incremental fashion, the smaller the firm the more number of employees were likely to be hired over the past three years. These results reflect the likelihood for a simulated firm that would have the same age, sector of activity, wage levels and, among others, infrastructure traits as an average firm but would have either a smaller or larger number of employees in the base year. These results here are consistent with international findings17 and can likely be partly explained by greater levels of substitution of labour for capital and technology among larger firms. Another possible explanation is that smaller firms are more likely to benefit from lax enforcement of regulations including labour and tax regulations, while larger firms generally spend more time dealing with public officials and red tape (Pagés et al. 2007).

Table 3 Correlates of job growth among basic firm-level features and overall business climate traits including wages, infrastructure, regulation and finance, in East Asia Pacific over the last 3 years (model 1) Full size table

Younger firms, particularly in China, Indonesia, Laos, Mongolia, Tonga and Vanuatu, appear to grow overall faster—a trend found globally (Evans 1987; Dutz et al. 2011; Ayyagari et al. 2011; Fox and Oviedo 2008; Shi and Michelitsch 2012). A possible explanation is that younger firms engage more frequently in introducing new technology or a new product (World Bank 2012). Large cities, while on one hand providing potential agglomeration effects, generally have higher levels of competition, on the other. Being located in the capital or in a city with over one million people is positively and significantly correlated with firm expansion in China, Fiji and Vietnam, i.e. larger cities were more likely to be growth poles. Yet in Indonesia and the Philippines, smaller cities were more likely to experience job growth.

In terms of sector of activity, there appears to be a bias in job growth towards service sector firms in the Pacific Island countries (except for Tonga). In China and Indonesia, it was manufacturing firms that were most likely to employ more workers. Other sectors such as construction and transportation were correlated with the strongest employment growth in several of the lower-middle income countries such as Lao, Mongolia, Timor-Leste and Vietnam.

Table 3 illustrates that being formally registered when firms’ began operations is positively and significantly correlated with employing more workers in China, Micronesia, Mongolia, the Philippines, Tonga and Vietnam. Only in Indonesia was this relationship significantly negative, where informality is the norm and less than one third of firms are formally registered when they start their business. At the same time, as firms increase in size so does the likelihood of formalising. Sole proprietorships (unincorporated businesses with one owner) appear less likely to hire more people.

Firms that are partially or fully owned by foreign individuals, companies or organisations are overall more likely to expand their firm size, particularly in several of the larger economies in the region—(see Pagés et al. (2007)) for similar results globally. A potential channel through which foreign owned firms can contribute to higher job growth is through greater acquisition of new technical and managerial skills as well as other benefits as a result of their greater integration in international value chains (World Bank 2012).

In terms of gender, there seems to be a consistent relationship across the region between a higher share of women within a firm and lower job growth, with Samoa as an exception. This can possibly be explained in part by females not being randomly distributed across sectors, but firms with 50% or more females are disproportionately concentrated in the sectors of retail and wholesale, garments, and hotels and restaurants. These are among the highest productivity sectors (requiring thus fewer workers) as descriptive data calculations indicate. Other factors may also play a role such as maternity leave and women being more likely to balance work with household tasks and caretaking of other household members (World Bank 2004; 2012).

Worker wages, which are calculated by dividing a firm’s total annual cost of labour by its total number of permanent full-time employees, are split here into terciles for each country. There is a significant relationship across all countries in the region, except China, between higher wage premiums and lower job growth. This can be often largely due to the fact that a firm that falls into the second or third tercile pays their workers on average about twice or triple as much as firms in the bottom tercile (the reference group). That is, firms in the bottom tercile account for the 33.3% of the lowest wage firms that, in principle, can hire twice or triple as many workers given their lower wages—while the model controls for different levels of earnings associated with firms being active in manufacturing, services, or other sectors. This can also be related to the nature of production, as lower wage firms (which are often lower-skilled and more labour-intensive) are more likely to hire in pace with firm expansion than higher wage firms (which are often higher-skilled and more capital-intensive).

Higher labour productivity (while often improving living standards in the longer term) appears more likely to destroy jobs than to create jobs across East Asia Pacific countries over the past three years. This can be due to more productive firms (measured here as a firm’s total annual sales divided by its number of employees) conducting their business in a more efficient way that requires fewer workers to produce an equivalent amount of goods or services. This negative relationship may also be explained in part by the majority of firms employing less than 15 workers in nearly all countries in the region (Table 2), while descriptive analysis here indicates that larger firms generally experience higher levels of productivity across the region18.

Similar to wages, it is worth noting that the overall negative relationship observed between productivity and employment reflects firm dynamics over a three year period, while it is possible that higher productivity may possibly lead in some firms—e.g. through a larger production line, new products or markets—to job creation in the longer term. That is, there is the potential for the shorter-term trade-off between job creation and productivity to be offset in the longer term as greater productivity can raise income levels, which in turn can contribute to the expansion of other economic activities and can absorb the slack of labour.

Exporting is positively and significantly correlated with a firm’s expansion, especially in larger economies such as China, Indonesia, Mongolia, the Philippines and Vietnam. These results here are in line with findings in sub-Saharan Africa (Fox and Oviedo 2008) and globally (Dutz et al. 2011; Shi and Michelitsch 2012). Yet exporting appears to have no statistically significant relationship within Pacific Island countries (Table 3). Being small and remote, Pacific Island countries can be more constrained in benefiting from agglomeration and are less connected to global trade. The export premium observed especially in larger economies can be associated with potentially greater learning related to working with providers and suppliers in international markets, i.e. possibly acquiring new technical and managerial skills and applying new technologies from abroad (Rankin et al. 2006; World Bank 2012; Movahedi and Gaussens 2012).

Firms in four countries in the region (Fiji, Mongolia, the Philippines and Vanuatu) appeared to still overall expand their firm size despite experiencing, on average, three or more power outages a month (for similar results across sub-Saharan Africa, see Aterido and Hallward-Driemeier 2008). A lack of reliable electricity infrastructure does not seem to have translated into an inevitable binding constraint to firm expansion, with some firms addressing the problem of power outages with their own generators, which about 25% or more of firms own or share in these four countries (see Table 2 on descriptive statistics). On the other hand, three or more power outages a month appear to significantly constrain firm growth in some countries in which firms have lower levels of generator ownership such as Laos (at about 12% ownership) and Samoa (at about 19% ownership).

Firms spending 5% or more of senior management’s time in a typical week dealing with government regulations (taxes, customs, labour regulations, licensing and registration) does not appear to be a very clear or strong correlate of job creation.

Firms’ expansion in China, Laos, the Philippines, Tonga and Vietnam seems to have significantly benefited from having a credit line or loan from a bank19, as it can improve their capacity to plan longer term and make investments. In Indonesia, however, this relationship was inverse and significant. This could possibly be related to very low levels of credit being the norm in Indonesia, as the country has the second lowest share of firms in the region with a credit line or loan at about 18% and the lowest share of firms in the region with a checking or savings account at about 50% (see Table 2). At the same time however, it is possible that in some cases potential influences on this specific indicator could go in both direction, as firms that are growing may possibly be more likely to qualify for, and thus have, a loan from a bank.

In terms of paying bribes, firms are asked if similar establishments are known to make any informal payments to public officials to operate whether for customs, taxes, licenses, regulations, services or the like, which helps mitigate downward bias in reporting bribes given potential social and legal stigma associated with direct reporting. Descriptive data illustrate that about 90% of firms in the region report not having to pay any bribes. Yet, since giving public officials payments has a relatively strong, positive correlation with job growth in several countries in the region, bribes do not appear to present a pressing constraint to creating jobs for many firms. In Vanuatu, however, paying bribes has a negative and significant correlation with job growth, although only 3.4% of firms reported such payments (see Table 2).

Regression model 2 and results

The following exercise consists of estimating a similar equation, controlling for the same indicators as the first model (Table 3), but the second model also includes information on whether a firm is government owned, uses email, has an external auditor, has an overdraft facility on their bank account, and was inspected by tax officials (Table 4). Estimating these models separately allows for robustness checks and to test the degree to which some of the control variables may be correlated with each other and move in unison. An example is that the second model includes a variable on email use (which often depends on the quality of electricity supply), but the correlates for power outages remain overall similar in both models. Similarly, the second model includes a variable for whether firms were inspected by tax officials (which could influence the prevalence of having to pay bribes), but the correlates for paying informal payments to officials remain overall consistent within both models.

Table 4 Correlates of job growth among basic firm-level features and overall business climate traits including wages, infrastructure, regulation and finance, in East Asia Pacific over the last 3 years (model 2) Full size table

The inclusion of a control for being a government owned firm, although not significant across all countries in the region, shows that private owned firms were more likely to grow (except in Tonga where the public sector is a large employer)20. Internet use is an enterprise trait that can be important at various business levels from spreading ideas and innovating to greater employment growth (World Bank 2004; Dutz et al. 2011). Across East Asia Pacific, using email to conduct business has a statistically significant and positive correlation with employment growth in six countries but a negative correlation in Fiji and Mongolia—two countries that are relatively less connected to international markets.

If a firm had its annual financial statement checked and certified by an external auditor last fiscal year, this could be a proxy for better planning, managing and operating their business, with results showing that such firms were overall more likely to have expanded, although this relationship was not always strong. Similar to a credit line or loan, firms with an overdraft facility on their bank account (which already captures having a bank account) more often create jobs, likely as overdraft protection can help to smooth business cycle fluctuations. Firms that reported being inspected by tax officials over the last year were significantly more likely to expand their business operations in China, Fiji, Indonesia, Micronesia, Timor-Leste and Vanuatu. This can be because tax inspection can be a proxy for a core component of a functioning regulatory and tax system, but the same system has the potential to also strain at times some firms with excessive time needed to deal with regulations and with requiring bribes.

Exploring variations in the results among sub-samples of firms, and conducting robustness checks

Estimations of various sub-samples, while verifying on a whole the results, show non-linearities in the correlates of overall business climate conditions by firm size, firm age, and sector of activity, with different types of firms responding at times differently to the same (or similar) business environment. They also reinforce the need for disaggregated analysis. Given smaller sample sizes for such disaggregated analysis and thus reduced variation, several Pacific Island countries had to be omitted from these split regressions and for the remaining countries significance levels were generally slightly lower than in the full second model. The overall negative relationship between productivity and job growth reduces among smaller and younger firms in some countries. In estimating the correlates for the sub-sample of micro firms only (with 5 or fewer employees) using the second model, a few important differences emerge: Higher levels of productivity were strongly correlated with increased job creation in the Philippines and Tonga, and slightly correlated in China; and micro firms with an overdraft facility on their bank account were much more likely to create jobs in the Philippines, Tonga and Vietnam. Pagés et al. (2007) similarly find that improved access to credit can increase employment growth, especially for smaller firms, and can thus help them transition into medium-size or large firms. In a firm age split model including only firms less than 10 years old using the same controls in the second model, one interesting difference is that younger firms with higher productivity were more likely to grow in the Philippines and Mongolia.

In analysing only manufacturing firms using the second model, overall results remain similar between manufacturing and non-manufacturing firms with a few exceptions: Filipino manufacturing firms in large cities or the capital seem to have grown faster than firms in other sectors in these areas; manufacturing firms, with higher shares of females seem to have grown faster in Mongolia and Tonga; and Mongolian manufacturing firms with higher productivity appear to have experienced significant and positive growth. In analysing only service sector firms, overall results are similar, although two differences were that service sector firms were less likely to hire more employees if they were foreign-owned in Indonesia and Mongolia, and if they had three or more power outages per month in Mongolia.

In the following, the second model is tested with pooled data, which is the most common approach in analysing job growth with enterprise survey data in spite of the associated limitations as outlined in the introduction. The country-specific analyses conducted in this paper help circumvent these limitations and can provide policymakers with information relevant for individual countries, while pooled regression analysis instead merges all variation observed across countries in Tables 3 and 4 into a single, averaged estimated coefficient. Nonetheless, in a pooled regression, as a robustness check, including all firm observations across East Asia Pacific (for all 12 countries with data) and including country fixed effects using the second model, the results—while largely shaped by conditions in China—show some similar overall trends on some of the correlates of employment growth: firms that grew most are more likely smaller, exporting and foreign-owned, and have lower wages and lower productivity21. Yet the regional results hide correlates of job growth that are unique not only within individual countries but also across sub-groups of countries. For example, job creation is overall strongly correlated with service sector firms in the group of Pacific Island countries, while being foreign-owned or exporting has a positive and statistically significant correlation with firm expansion in the group of larger economies in the region including China, Indonesia, the Philippines and Vietnam (in contrast to Pacific Island countries). In addition, a probit model is created with job creation as the dependent variable (1 or 0) and a separate probit model with job destruction as the dependent variable (1 or 0), which is in contrast to the average annualised job growth rate of firms as in the previous models. Results suggest that smaller firms are more likely the largest contributor to job creation, while larger firms are the largest contributor to job destruction in the region. However, small firms create and shed most jobs at the global level (World Bank 2012). Government-owned firms are not only less likely to create jobs but are also more likely to shed jobs, especially when China is withdrawn from the regional sample, so that job creation at the regional level appears to be largely private-sector led and particularly strong among foreign-owned firms. Higher wages not only likely deter creating new jobs but also likely support shedding jobs. Results suggest that credit not only supports job growth but also may function as a possible financial shock absorber to mitigate job loss across the region (results for the pooled regressions are in Table 5 in the Appendix for interested readers).

Table 5 Correlates of job growth, job creation and job destruction among basic firm-level features and overall business climate traits, East Asia Pacific average over the last 3 years (model 3) Full size table

To reiterate, when analysing enterprise survey data, no causal relationships can be established between job creation and the range of business climate indicators irrespective of the statistical model employed, as all models have unobservables (as outlined earlier) that can interact with independent variables and cannot all be fully controlled for22. While strong differences arise across countries and sub-groups of countries and while it is likely that the strength of correlates over the past three years will not be identical over the coming years, the country-specific analyses nonetheless can help identify some trends and illustrate that firms within many East Asian and Pacific countries with the following traits grew over this period:

Most job creation Micro and small-sized firms/Firms with lower wages/Exporting firms/Foreign-owned firms/Firms with a credit line or loan, and those with an overdraft facility

Least job creation Large firms/Sole proprietorships/Firms with higher wages/Government-owned firms/Firms spending 5+ % of time on regulations/Firms with higher levels of productivity



In general, results suggest that an overall weak business climate in a number of countries in the region can help sustain the distribution of enterprises towards smaller firms. Also, given that most job growth was experienced by small firms, which are generally more labour-intensive and less productive, this could raise concerns in the longer term about the efficient allocation of resources and aggregate productivity growth.