This study aims to identify the productivity determinants of manufacturing micro firms, emphasizing on regional and industrial factors. A cross-classified multilevel model is employed using the Economic Census of 2010 from Ecuador. Results show (90.1%) that the heterogeneity of the total factor productivity of micro formal firms of the manufacturing sector is mainly due to differences across firms. The remaining variation of the TFP is explained to a larger extent by the industrial context (5.8%) than the geographical context (4.1%). Among firm characteristics, information and communication technologies, credit and training are important drivers of productivity. Despite this, very few micro firms use the Internet, have credit access or engage in training in Ecuador. Moreover, micro firms benefit from agglomeration economies derived from specialization, diversity and density that they themselves generate.

This paper focuses on the relationship between imports, innovation and population agglomeration within regions in Colombia. The main aim is to identify the source of trade that shapes the relationship between innovation and agglomeration, by distinguishing imports ac­cording to levels of technological intensity. This study attempts to bridge two factors that have been studied separately: trade on the one hand; science, technology and innovation activity (STI), on the other. To control for unobserved heterogeneity, the Least Square Dummy Variable estimator with robust standard errors was employed. The results show that the technological intensity of imports has an impact on the agglomeration effect of STI activity. Moreover, the effect of STI activity on intra-regional agglomeration conditioned by imports varies according to regional characteristics.

PurposeThe service industry has become an important sector for the economic growth, particularly in developing countries. In this context, the aim of this article is to compare the productivity determinants across firms operating in low and high knowledge intensity service sectors (low knowledge intensive sectors (LKIS) and high knowledge intensive sectors (HKIS)) in Ecuador.Design/methodology/approachThe authors use a two-step estimation method. The firm productivity is estimated in the first step and the productivity determinants in the second step. To achieve the objective, the authors use an unbalanced panel database on the financial statements from formal Ecuadorian firms for the period 2007–2018.FindingsThe authors’ results show that LKIS firms are slightly more labor-intensive compared to HKIS firms. Productivity determinants are similar across HKIS and LKIS firms, except for exports and market concentration. HKIS firms are more productive when the competition level is low, indicating that higher market power is associated with higher productivity. The influence of taxes on productivity depends on firm size. Small and medium-sized firms are more negatively affected than large firms.Practical implicationsTaxes should be designed considering the size of the companies, since these could affect their productivity. Thus, lower taxes to small and medium firms may reduce firm size inequality. In addition, the acquired knowledge of HKIS should be spread to other firms becoming a positive externality instead of an entry barrier.Originality/valueDespite the productivity determinants of the service sector has been recently explored, in contrast to the manufacturing sector, individual and contextual determinants are less identified. In this paper the authors use a large set of firm characteristics that might affect productivity in service firms.

The COVID-19 pandemic has revealed the state of underlying conditions of countries in terms of health system, sanitary infrastructure, governance, among others. This study aims to classify countries using COVID-19-related variables such as the lethality rate, the contagion growth rate, the stringency index, and underlying conditions of countries directly related to COVID-19 such as access to clean water, hospital beds per 10000 inhabitants, government effectiveness index, population older than 65 years old and economic growth rate. To determine the clusters of a set of countries from all continents (29 from Africa, 35 from Asia, 35 from Europe, 11 from North America, 2 from Oceania and 8 from South America), the k-means partitioning method is used. This approach consists in constructing partitions and evaluate their intra-class and inter-class similarity. Based on the results, three clusters are identified: i. Severely affected countries with high stringency and moderate capacity, ii. Moderately affected countries with moderate stringency and high capacity and iii. Severely affected countries with low stringency but low capacity.

This study analyses the influence of city size on life satisfaction among the Ecuadorian population. It distinguishes rural from urban residents and looks at the effect of environmental management. Using individual and canton-level variables, an ordinal logit model is estimated. Results suggest that individuals living in the most populated cantons report a lower level of life satisfaction. This effect varies for urban and rural residents. Environmental management is positive for life satisfaction.